HORIZONTAL WELL CUTTINGS BED PROCESSING METHOD AND DEVICE

Abstract

The present disclosure discloses a horizontal well cuttings bed processing method and device. The method includes: based on drilling engineering information of a horizontal well, predicting a distribution pattern of a cuttings bed throughout a drilling process, determining a cuttings bed height risk level in each well section, and outputting a cuttings bed removal solution associated with the well section. According to the present disclosure, processing accuracy and processing efficiency of the cuttings bed in a horizontal well can be improved, and accumulation of the cuttings bed in the horizontal well can be effectively resolved.

Description

BACKGROUND OF THE DISCLOSURE

1. Field of the Disclosure

The present disclosure relates to the technical field of petroleum drilling, and in particular to a horizontal well cuttings bed processing method and device.

2. Description of Related Art

At present, as exploration and development difficulties are increased, a new drilling technology and a new process emerge and develop increasingly, a horizontal well drilling technology is favored by the drilling world because of characteristics of a high reservoir discovery rate, a high yield, a low oil cost per ton, and the like, a proportion of wells drilled in this manner is increased year by year. Especially, after unconventional oil reservoirs such as fractured oil reservoirs, thin oil reservoirs, low-permeability oil reservoirs, and the like are successfully used, an exploitation degree of the oil reservoirs is greatly increased. In addition, a horizontal well technology plays an essential role in increasing the yield and the recovery efficiency, a stable yield of the horizontal well technology is 2-5 times greater than a yield of a vertical well. The horizontal well technology has gradually become an important means for modern oil and gas exploration and development and become a main force for development of various oil fields.

Although the horizontal well drilling technology has many advantages, one of disadvantages is that cuttings in a horizontal well section need to be removed, and a serious drilling accident may be caused in case of poor wellbore purification, which needs to be concerned sufficiently.

Because of the particularity (a well inclination angle is in a range of approximately 90 degrees) of a wellbore structure of the horizontal well section, a remove track of cuttings in horizontal annulus under the comprehensive action of various forces is obviously different from a remove track in a vertical well section. When a return speed of drilling liquid is low, the cuttings easily fall on a lower edge of the annulus of the wellbore and is gradually accumulated to form a cuttings bed, so that a series of complicated engineering problems may be caused.

At present, conventional cleaning manners include: short-trip with downhole tools or long-distance sliding sleeves; increase of a discharge capacity of the drilling liquid; adjustment of a rheological property of the drilling liquid; increase of a rotation speed of a drilling rod, and the like. However, such sand removal manners are determined based on the experience of workers on site, and there is no complete cuttings bed cleaning solution.

SUMMARY OF THE DISCLOSURE

An embodiment of the present disclosure provides a horizontal well cuttings bed processing method, to improve processing accuracy and processing efficiency of the cuttings bed in a horizontal well, effectively resolving a problem of accumulation of the cuttings bed in a horizontal well, and improving the development benefit of the horizontal well. The method includes:

• • predicting a distribution pattern of the cuttings bed throughout a drilling process based on drilling engineering information of the horizontal well, where the distribution pattern of the cuttings bed throughout the drilling process is used for describing predicted cuttings accumulation and remove of the cuttings bed in each well section;
  • predicting a running position of a cuttings cleaning tool for each well section based on the distribution pattern of the cuttings bed throughout the drilling process;
  • calculating an actual cuttings bed height in each well section based on logging data during the drilling process;
  • correcting the predicted running position of the cuttings cleaning tool for each well section based on the actual cuttings bed height in each well section, to obtain correction data of the running position of the cuttings cleaning tool for each well section;
  • determining a cuttings bed height risk level in each well section based on a percentage of drilled returned cuttings, a deflection degree of drilled cuttings particle size distribution, and a change rate of a drilling hook load in the drilling process;
  • associating different cuttings bed height risk levels with different cuttings bed removal solutions; and
  • for each well section, outputting the correction data of the running position of the cuttings cleaning tool for the well section and a cuttings bed removal solution associated with the cuttings bed height risk level for the well section.

An embodiment of the present disclosure provides a horizontal well cuttings bed processing device, to improve processing accuracy and processing efficiency of the cuttings bed in a horizontal well, effectively resolving a problem of accumulation of the cuttings bed in a horizontal well, and improving the development benefit of the horizontal well. The device includes:

• • a cuttings bed distribution pattern prediction module, configured to predict a distribution pattern of a cuttings bed throughout a drilling process based on drilling engineering information of a horizontal well, where the distribution pattern of the cuttings bed throughout the drilling process is used for describing predicted cuttings accumulation and remove of the cuttings bed in each well section;
  • a cuttings cleaning tool running position prediction module, configured to predict a running position of a cuttings cleaning tool for each well section based on the distribution pattern of the cuttings bed throughout the drilling process;
  • an actual cuttings bed height calculation module, configured to calculate an actual cuttings bed height in each well section based on logging data during the drilling process;
  • a cuttings cleaning tool running position correction module, configured to correct the predicted running position of the cuttings cleaning tool for each well section based on the actual cuttings bed height in each well section, to obtain correction data of the running position of the cuttings cleaning tool for each well section;
  • a well-section cuttings bed height risk level determining module, configured to determine the cuttings bed height risk level in each well section based on a percentage of the drilled returned cuttings, the deflection degree of drilled cuttings particle size distribution, and the change rate of the drilling hook load in the drilling process;
  • a cuttings bed removal solution association module, configured to associate different cuttings bed height risk levels with different cuttings bed removal solutions; and
  • a data output module, configured to output, for each well section, the correction data of the running position of the cuttings cleaning tool for the well section and a cuttings bed removal solution associated with the cuttings bed height risk level for the well section.

An embodiment of the present disclosure further provides a computer equipment, including a memory, a processor, and a computer program stored in the memory and runnable on the processor. When the processor executes the computer program, the above method for horizontal well cuttings bed processing is implemented.

An embodiment of the present disclosure further provides a computer-readable storage medium. The computer-readable storage medium stores a computer program. When the computer program is executed by a processor, the above method for horizontal well cuttings bed processing is implemented.

An embodiment of the present disclosure further provides a computer program product. The computer program product includes a computer program. When the computer program is executed by a processor, the above method for horizontal well cuttings bed processing is implemented.

In the embodiment of the present disclosure, predicting a distribution pattern of a cuttings bed throughout a drilling process based on drilling engineering information of a horizontal well, where the distribution pattern of the cuttings bed throughout the drilling process is used for describing the predicted cuttings accumulation and remove of the cuttings bed in each well section; predicting a running position of a cuttings cleaning tool for each well section based on the distribution pattern of the cuttings bed throughout the drilling process; calculating an actual cuttings bed height in each well section based on logging data during the drilling process; correcting the predicted running position of the cuttings cleaning tool for each well section based on the actual cuttings bed height in each well section, to obtain correction data of the running position of the cuttings cleaning tool for each well section; determining a cuttings bed height risk level in each well section based on a percentage of drilled returned cuttings, a deflection degree of drilled cuttings particle size distribution, and a change rate of a drilling hook load in the drilling process; associating different cuttings bed height risk levels with different cuttings bed removal solutions; and for each well section, outputting the correction data of the running position of the cuttings cleaning tool for the well section and a cuttings bed removal solution associated with the cuttings bed height risk level for the well section. Compared with the technical solution in which only a conventional cleaning manner can be manually formulated in the prior art, the distribution pattern of the cuttings bed throughout the drilling process is predicted, and different cuttings bed removal solutions are carried out for different cuttings bed height risk levels, so that the cuttings bed in the horizontal well is processed by integrating pre-drilling simulation prediction, drilling diagnosis and evaluation, and cuttings removal operation guidance, without the help of manpower anymore, the running position of the cuttings cleaning tool can be automatically adjusted, and a cuttings bed cleaning solution is automatically generated. Therefore, a problem that mistakes and omissions cannot be avoided in manual work in the prior art is resolved, the accuracy and the efficiency of the cuttings bed processing in the horizontal well are improved, the problem of accumulation of the cuttings bed in the horizontal well is effectively resolved, and a development benefit of the horizontal well is improved.

BRIEF DESCRIPTION OF THE DRAWINGS

To describe technical solutions in embodiments of the present disclosure or in the prior art more clearly, the following briefly describes accompanying drawings required for describing the embodiments or the prior art. Apparently, the accompanying drawings in the following description show merely some embodiments of the present disclosure, and a person of ordinary skill in the art may derive other drawings from these accompanying drawings without creative efforts. In the accompanying drawings,

FIG. 1 is a schematic flowchart of a method for horizontal well cuttings bed processing according to an embodiment of the present disclosure;

FIG. 2 is a schematic structural diagram of a device for horizontal well cuttings bed processing according to an embodiment of the present disclosure;

FIG. 3 is a specific example diagram of a device for horizontal well cuttings bed processing according to an embodiment of the present disclosure;

FIG. 4 is a specific example diagram of a method for horizontal well cuttings bed processing according to an embodiment of the present disclosure;

FIG. 5 is a schematic diagram of a computer equipment according to an embodiment of the present disclosure;

FIG. 6 is a specific example diagram of a device for horizontal well cuttings bed processing according to an embodiment of the present disclosure; and

FIG. 7 is a specific example diagram of a device for horizontal well cuttings bed processing according to an embodiment of the present disclosure.

DETAILED DESCRIPTION OF THE DISCLOSURE

To make the objectives, technical solutions, and advantages of embodiments of the present disclosure more clear, the embodiments of the present disclosure will be further described in detail below with reference to the accompanying drawings. The exemplary embodiments of the present disclosure and descriptions thereof are used to explain the present disclosure, but are not used as a limitation on the present disclosure.

The term “and/or” in this specification describes only an association relationship and indicates that three relationships may exist. For example, A and/or B may indicate the following three cases: Only A exists, both A and B exist, and only B exists. In addition, the term “at least one” in this specification means any one of a plurality or any combination of at least two of a plurality, for example, including at least one of A, B, and C, which can mean including any one or more elements selected from a set composed of A, B and C.

In the description of this specification, the used “include”, “comprise”, “has”, “contain”, and the like are all open terms, which mean including but not limited to. Description with reference to the term “one embodiment,” “a specific embodiment,” “some embodiments,” “such as,” or the like in the means that a specific feature, structure, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of this application. In this specification, illustrative expressions of these terms do not necessarily refer to a same embodiment or example. Moreover, the specific feature, structure, or characteristic described may be combined in any suitable manner in any one or more embodiments or examples. A sequence of steps in each embodiment is used to schematically illustrate implementation of this application. The sequence of steps is not limited and may be adjusted appropriately as needed.

As exploration and development difficulties are increased, a new drilling technology and a new process emerge and develop increasingly, the horizontal well drilling technology is favored by the drilling industry because of characteristics of a high reservoir discovery rate, a high productivity, a low oil cost per ton, and the like, a proportion of wells drilled completed in this manner is increased year by year, especially with the successful application in unconventional oil reservoirs such as fractured oil reservoirs, thin oil reservoirs, low-permeability oil reservoirs, an exploitation degree of the oil reservoirs is greatly increased. At the same time, a horizontal well technology plays an essential role in increasing the production and the recovery efficiency rates, a stable production of the horizontal well technology is 2-5 times greater than a production of a vertical well technology. The horizontal well technology has gradually become an important means for modern oil and gas exploration and development and become a main force for development of various oil fields.

Although the horizontal well drilling technology has many advantages, one of its disadvantages is that cuttings in a horizontal well section need to be removed, and a serious drilling accident may be caused in case of poor wellbore purification, which needs to be concerned sufficiently. Because of the particularity (a well inclination angle is in a range of approximately 90 degrees) of a wellbore structure of the horizontal well section, a remove track of cuttings in horizontal annulus under the comprehensive action of various forces is obviously different from a remove track in a vertical well section. When a return speed of drilling liquid is low, the cuttings easily fall on a lower edge of the annulus of the wellbore and is gradually accumulated to form a cuttings bed, so that a series of complicated engineering problems may be caused.

The existence of a cuttings bed brings many safety hazards to drilling construction and seriously threatens safe drilling, which are mainly reflected in the following aspects.

• • 1. The cuttings bed easily causes a drill to produce a high friction and high torque, or even twist-off of the drill.
  • 2. The cuttings bed may cause a rate of penetration to decrease. Due to loose arrangement of cuttings particles in the cuttings bed, keyways are easily formed to cause backing pressure. As a result, a drilling pressure cannot be fully applied to a bit. In addition, a resistance to lifting and lowering the drill is increased, which reduces drilling efficiency.
  • 3. The cuttings bed easily causes accidents such as jamming of the drill and the like, so that a project progress is slow, and a drilling period is prolonged.
  • 4. The cuttings bed may also cause problems such as a difficulty in well logging tool running, a difficulty in placing a casing and cementing, poor well cementing quality, and the like.
  • 5. Because the drill is not centered in the horizontal well section, the cuttings are repeatedly crushed into finer particles by the drill, content of a solid phase of annular drilling liquid is increased, an annular gap is reduced, an oval wellbore is formed, and an increase in pump pressure is easily caused.
  • 6. The cuttings bed easily causes a lower part of the drill to generate ball-up, so that the drilling is limited. In addition, if the drilling liquid is not sufficiently circulated before the pump is stopped, the cuttings sink to form a sand bridge after the pump is stopped, so that sand blockage is caused, and a potential safety hazard exists if drilling is continued.

Conventional cleaning manners include: short-trip with downhole tools or long-distance sliding sleeves; increase of a discharge capacity of the drilling liquid; adjustment of a rheological property of the drilling liquid; increase of a rotation speed of a drilling rod, and the like. However, such sand removal manners are determined based on the experience of workers on site, and there is no complete cuttings bed cleaning solution. Therefore, a complete system solution is required for determining, analyzing, cleaning and clearing the cuttings bed, to ensure on-site drilling production.

To resolve the above problems, an embodiment of the present disclosure provides a method for horizontal well cuttings bed processing, to improve processing accuracy and processing efficiency of the cuttings bed in the horizontal well, effectively resolving a problem of accumulation of the cuttings bed in the horizontal well, and improving a development benefit of the horizontal well. Refer to FIG. 1, the method may include:

• • Step 101: Predict a distribution pattern of a cuttings bed throughout a drilling process based on drilling engineering information of a horizontal well, where the distribution pattern of the cuttings bed throughout the drilling process is used for describing predicted cuttings accumulation and remove of the cuttings bed in each well section;
  • Step 102: Predict a running position of a cuttings cleaning tool for each well section based on the distribution pattern of the cuttings bed throughout the drilling process;
  • Step 103: Calculate an actual cuttings bed height in each well section based on logging data during the drilling process;
  • Step 104: Correct the predicted running position of the cuttings cleaning tool for each well section based on the actual cuttings bed height in each well section, to obtain correction data of the running position of the cuttings cleaning tool for each well section;
  • Step 105: Determine a cuttings bed height risk level in each well section based on a percentage of drilled returned cuttings, a deflection degree of drilled cuttings particle size distribution, and a change rate of a drilling hook load in the drilling process;
  • Step 106: Associate different cuttings bed height risk levels with different cuttings bed removal solutions; and
  • Step 107: For each well section, output the correction data of the running position of the cuttings cleaning tool for the well section and a cuttings bed removal solution associated with the cuttings bed height risk level for the well section.

In the embodiment of the present disclosure, predicting a distribution pattern of a cuttings bed throughout a drilling process based on drilling engineering information of a horizontal well, where the distribution pattern of the cuttings bed throughout the drilling process is used for describing the predicted cuttings accumulation and remove of the cuttings bed in each well section; predicting a running position of a cuttings cleaning tool for each well section based on the distribution pattern of the cuttings bed throughout the drilling process; calculating an actual cuttings bed height in each well section based on logging data during the drilling process; correcting the predicted running position of the cuttings cleaning tool for each well section based on the actual cuttings bed height in each well section, to obtain correction data of the running position of the cuttings cleaning tool for each well section; determining a cuttings bed height risk level in each well section based on a percentage of drilled returned cuttings, a deflection degree of drilled cuttings particle size distribution, and a change rate of a drilling hook load in the drilling process; associating different cuttings bed height risk levels with different cuttings bed removal solutions; and for each well section, outputting the correction data of the running position of the cuttings cleaning tool for the well section and a cuttings bed removal solution associated with the cuttings bed height risk level for the well section. Compared with the technical solution in which only a conventional cleaning manner can be manually formulated in the prior art, the distribution pattern of the cuttings bed throughout the drilling process is predicted, and different cuttings bed removal solutions are carried out for different cuttings bed height risk levels, so that cuttings bed in a horizontal well is processed by integrating pre-drilling simulation prediction, drilling diagnosis and evaluation, and cuttings removal operation guidance, without the help of manpower anymore, the running position of the cuttings cleaning tool can be automatically adjusted, and a cuttings bed cleaning solution is automatically generated. Therefore, a problem that mistakes and omissions cannot be avoided in manual work in the prior art is resolved, the processing accuracy and the processing efficiency of the cuttings bed in the horizontal well are improved, the problem of accumulation of the cuttings bed in a horizontal well is effectively resolved, and a development benefit of the horizontal well is improved.

In specific implementation, first, the distribution pattern of the cuttings bed throughout the drilling process is predicted based on the drilling engineering information of the horizontal well. The distribution pattern of the cuttings bed throughout the drilling process is used for describing the predicted cuttings accumulation and remove of the cuttings bed in each well section.

In the embodiment, the predicting a distribution pattern of a cuttings bed throughout a drilling process based on drilling engineering information of a horizontal well includes:

based on a finite volume method and in combination with the drilling engineering information, calculating and simulating a drilling time axis, to obtain the predicted distribution pattern of the cuttings bed throughout the drilling process.

In an embodiment, the distribution pattern of the cuttings bed throughout the drilling process can be predicted and calculated based on the finite volume method as follows:

• • Step 1: The cuttings and the drilling liquid satisfy the following mass conservation equation and momentum conservation equation:

$\begin{array}{cc}\{\begin{array}{c}\frac{\partial }{\partial t}\left[\left(1-\alpha \right){\rho }_l\right]+\frac{\partial }{\partial x}\left[\left(1-\alpha \right){\rho }_l{v}_l\right]=0\\ \frac{\partial }{\partial t}\left(\alpha {\rho }_s\right)+\frac{\partial }{\partial x}\left(\alpha {\rho }_s{v}_s\right)=0\\ \frac{\partial }{\partial t}\left[\left(1-\alpha \right){\rho }_l{v}_l+\alpha {\rho }_s{v}_s\right]+\frac{\partial }{\partial x}\left[\left(1-\alpha \right){\rho }_l{v}_l^2+\alpha {\rho }_s{v}_s^2+p\right]=s_m\end{array}& \left(1\right)\end{array}$

• • where α represents a volume fraction of the cuttings in the horizontal well section and is dimensionless; ρ_l represents density of the drilling liquid in kg/m3: ρ_s represents a density of the cuttings in kg/m³; ν_l represents a flow velocity of the drilling liquid in m/s; ν_s represents a flow velocity of the cuttings particles in m/s; p represents a pressure of the drilling liquid in pa; s_m represents a source item in pa;

$\frac{\partial }{\partial t}$

• • represents a partial derivative of a parameter with respect to time in the unit of s⁻¹;

$\frac{\partial }{\partial x}$

• • represents a partial derivative of a parameter with respect to space in the unit of m⁻¹.
  • Step 2: Take intermediate variables W_l, W_s, W_p, and a matrix F, with expressions of respectively as follows:

$\begin{array}{cc}\{\begin{array}{c}{W}_l={\rho }_l{\alpha }_l\\ W_s={\rho }_s{\alpha }_s\\ W_P={\rho }_l{\alpha }_l{u}_l+{\rho }_s{\alpha }_s{u}_s\end{array}& \left(2\right)\end{array}$ $\begin{array}{cc}F=\left(\begin{array}{ccc}{F}_l\left(1,1\right)& F_s\left(1,1\right)& P\left(1,1\right)\\ F_l\left(2,1\right)& F_s\left(2,1\right)& P\left(2,1\right)\\ F_l\left(3,1\right)& F_s\left(3,1\right)& P\left(3,1\right)\end{array}\right)=\left(\begin{array}{ccc}{\alpha }_l{\rho }_l{u}_l& 0& 0\\ 0& {\alpha }_s{\rho }_s{u}_s& 0\\ {\alpha }_l{\rho }_l{u}_l^2& {\alpha }_s{\rho }_s{u}_s^2& p\end{array}\right)& \left(3\right)\end{array}$

• • where W_l, W_s, W_p, and F are the intermediate variables; α_l represents a volume fraction of the drilling liquid and is dimensionless; α_s represents a volume fraction of the cuttings and is dimensionless; u_l represents the flow velocity of the drilling liquid in the unit of m/s; and u_s represents the flow velocity of the cuttings particles in the unit of m/s.
  • Step 3: Flux changes of conservation variables of a liquid phase, a solid phase, and a mixed momentum term satisfy the following condition:

$$\begin{gathered} \begin{array}{cc}\frac{\partial W_l}{\partial t}=-\left(\frac{\partial F_l\left(1,1\right)}{\partial x}+\frac{\partial F_s\left(1,1\right)}{\partial x}+\frac{\partial P\left(1,1\right)}{\partial x}\right)\text{ \\ ∂Ws∂t=-(∂Fl(2,1)∂x+∂Fs(2,1)∂x+∂P⁡(2,1)∂x)⁢ \\ ∂WP∂f=-(∂Fl(3,1)∂x+∂Fs(3,1)∂x+∂P⁡(3,1)∂x)-sm}& \left(4\right)\end{array} \end{gathered}$$

• • Step 4: After discretization, iterative equation forms:

The Liquid Phase:

$\begin{array}{cc}{W_l}_i^j-{W_{\mathrm{old}-l}}_i^j=-\frac{\Delta t}{\Delta x}\left(\begin{array}{c}\left({F_l\left(1,j+1\right)}_i^{j+1}-{F_l\left(1,j\right)}_i^j\right)+\\ \left({F_s\left(1,j+1\right)}_i^{j+1}-{F_s\left(1,j\right)}_i^j\right)+\\ \left({P\left(1,j+1\right)}_i^{j+1}-{P\left(1,j\right)}_i^j\right)\end{array}\right)& \left(5\right)\end{array}$

The Solid Phase:

$\begin{array}{cc}{W_s}_i^j-{W_{\mathrm{old}-s}}_i^j=-\frac{\Delta t}{\Delta x}\left(\begin{array}{c}\left({F_l\left(2,j+1\right)}_i^{j+1}-{F_l\left(2,j\right)}_i^j\right)+\\ \left({F_s\left(2,j+1\right)}_i^{j+1}-{F_s\left(2,j\right)}_i^j\right)+\\ \left({P\left(2,j+1\right)}_i^{j+1}-{P\left(2,j\right)}_i^j\right)\end{array}\right)& \left(6\right)\end{array}$

The Mixed Momentum Term:

$\begin{array}{cc}{W_P}_i^j-{W_{\mathrm{old}-P}}_i^j=-\frac{\Delta t}{\Delta x}\left(\begin{array}{c}\left({F_l\left(3,j+1\right)}_i^{j+1}-{F_l\left(3,j\right)}_i^j\right)+\\ \left({F_s\left(3,j+1\right)}_i^{j+1}-{F_s\left(3,j\right)}_i^j\right)+\\ \left({P\left(3,j+1\right)}_i^{j+1}-{P\left(3,j\right)}_i^j\right)\end{array}\right)-\Delta t·s_m& \left(7\right)\end{array}$

• • where subscripts i and old−i respectively represent parameter values of a i well section and a old−iwell section; superscripts j and j+1 respectively represent parameter values of well sections at a t time point and a t+Δt time point: further, old−li represents a value of an intermediate variable W_l of the liquid phase in a i well section at a j time point; old−si represents a value of an intermediate variable W_s of the solid phase in a i well section at a j time point; old−Pi represents a value of an intermediate variable W_p of a pressure in a i well section at a j time point; li represents a value of an intermediate variable W_l of the liquid phase in a i well section at a j+1 time point; si represents a value of an intermediate variable W_s of the solid phase in a i well section at a j+1 time point; and Pi represents a value of an intermediate variable W_p of a pressure in a i well section at a j+1 time point.

The liquid phase, the solid phase, and the mixed phase respectively represent a drilling liquid portion, cuttings portion, and a mixed portion of the drilling liquid and cuttings in the well section.

• • Step 5: Update a flux (namely, the intermediate variable F) in the drilling well section of each horizontal annulus within a time interval At, and then perform transverse calculation simulation by using a time axis, to obtain the distribution pattern of the cuttings bed throughout the drilling process, where the distribution pattern of the cuttings bed throughout the drilling process may be used for describing the cuttings accumulation and remove throughout the drilling process.

In specific implementation, after the distribution pattern of the cuttings bed throughout the drilling process is predicted based on the drilling engineering information of the horizontal well, the running position of the cuttings cleaning tool for each well section is predicted based on the distribution pattern of the cuttings bed throughout the drilling process.

In an embodiment, design of arrangement of the cuttings cleaning tool for cuttings deposition in key well sections (such as a horizontal well section and a highly deviated well section) can be performed based on the distribution pattern of the cuttings bed throughout the drilling process predicted before drilling, such as the prediction of the running position of the cuttings cleaning tool for each well section.

For example, if the predicted cuttings bed height before drilling is high, it can be learned that wellbore cleaning tools need to be densely arranged. If the cuttings bed height is low, it can be learned that an arrangement distance for the wellbore cleaning tools needs to be increased properly.

In specific implementation, after the running position of the cuttings cleaning tool for each well section is predicted based on the distribution pattern of the cuttings bed throughout the drilling process, the actual cuttings bed height in each well section is calculated based on the logging data in the drilling process.

In specific implementation, after the actual cuttings bed height in each well section is calculated based on the logging data during the drilling process, the predicted running position of the cuttings cleaning tool for each well section is corrected based on the actual cuttings bed height in each well section, to obtain correction data of the running position of the cuttings cleaning tool for each well section.

In an embodiment, the logging data in the drilling process may include: a well depth, a drilling rate, a drilling liquid density, a pump pressure, a discharge, a wellbore structure, a well trajectory, a drill assembly, a percentage of returned cuttings, cuttings particle size distribution, and hook load change. The parameters of the well depth, the drilling rate, the drilling liquid density, the discharge, the wellbore structure, and the like are used as input parameters for calculation of the actual cuttings bed height of each well section. In addition, a model of the distribution pattern of the cuttings bed throughout the drilling process is corrected by contrast with the percentage of the returned cuttings, the cuttings particle size distribution, and the hook load change, to obtain the correction data of the running position of the cuttings cleaning tool for each well section.

In specific implementation, after the predicted running position of the cuttings cleaning tool for each well section is corrected based on the actual cuttings bed height in each well section, to obtain correction data of the running position of the cuttings cleaning tool for each well section, the cuttings bed height risk level in each well section is determined based on the percentage of the drilled returned cuttings, the deflection degree of drilled cuttings particle size distribution, and the change rate of the drilling hook load in the drilling process.

In an embodiment, the determining a cuttings bed height risk level in each well section based on a percentage of drilled returned cuttings, a deflection degree of drilled cuttings particle size distribution, and a change rate of a drilling hook load in the drilling process includes:

• • pre-establishing a cuttings bed height risk matrix, where the cuttings bed height risk matrix takes a change rate of an initial drilling hook load as an abscissa, a deflection degree of initial drilled cuttings particle size distribution as an ordinate, and a percentage of initial returned cuttings as a matrix size;
  • dividing the cuttings bed height risk matrix, and determining the cuttings bed height risk level associated with each divided cuttings bed height risk matrix; and
  • matching the percentage of the drilled returned cuttings, the deflection degree of the drilled cuttings particle size distribution, and the change rate of the drilling hook load in the drilling process with each divided cuttings bed height risk matrix, to obtain the cuttings bed height risk level in each well section.

In a specific embodiment, refer to the following formula. The percentage of the returned cuttings may be defined as a ratio of the mass of the cuttings generated by drilling to the mass of returned cuttings from a wellhead.

$\begin{array}{cc}{M}_{sum}={\int }_{t_0}^{t_1}\mathrm{vt}{\rho }_{\mathrm{cuttings}}\frac{\pi D^2}{4}\mathrm{dt}& \left(8\right)\end{array}$ $\begin{array}{cc}\alpha =\frac{M_{real}}{M_{sum}}\times 100\%& \left(9\right)\end{array}$

• • where M_sum is a total amount of the cuttings generated by drilling in Δt time; v is the drilling rate; t is time; ρ_cuttings is a density of the cuttings at this time (related to a stratum drilled in the well); D is a diameter of a bit; α is the percentage of the returned cuttings; and M_real is an amount of return cuttings in the well in the Δt time.

Further, the percentage of the returned cuttings that reaches a preset value (such as 80%) can be defined as a safe drilling sign, and no additional sand cleaning operation is needed during drilling.

In a specific embodiment, the cuttings particle size distribution of the solid phase of the drilling liquid (namely, the deflection degree of the drilled cuttings particle size distribution) is a statistic of the diameter of the returned wellbore cuttings particles, the diameter of the particles may be a mean diameter of three axes of the particles, and a distribution graph of the cuttings particle size of the solid phase of the drilling liquid is drawn.

Further, the distribution graph of the cuttings particle size of the solid phase of the drilling liquid presents normal distribution in a normal drilling process. When a cuttings cleaning degree is relatively low, the distribution graph of the cuttings particle size is in a left deflection form. When the cuttings cleaning degree is relatively high, the distribution graph of the cuttings particle size is in a right deflection form.

Further, refer to the following formula. Cuttings cleaning effect may be represented by the deflection degree. As a left deflection degree is higher, the cuttings cleaning efficiency is lower. As a right deflection degree is higher, the cuttings cleaning efficiency is higher.

$\begin{array}{cc}\beta =\frac{L}{d_2-d_1}\times 100\%& \left(10\right)\end{array}$

• • where β is the deflection degree; L is a deflection distance; d₂ is a maximum diameter of the cuttings particles; and d₁ is a smallest diameter of the cuttings particles.

In a specific embodiment, refer to the following formula, the hook load change is derived from an increase in small solid particles during drilling, which is caused by repeated breaking of the cuttings. As a change rate of the hook load is greater, the cuttings cleaning effect is low.

$\begin{array}{cc}{G}_1=Mg-{\rho }_1\mathrm{gV}& \left(11\right)\end{array}$ $\begin{array}{cc}\eta =\frac{G_{real}}{G_1}\times 100\%& \left(12\right)\end{array}$

• • where η is the change rate of the hook load; G₁ is a theoretical load; M is a total mass of the drill; ρ₁ is a density of the drilling liquid; V is a total volume of the drill; and G_real is an actual load.

In an embodiment, in the pre-establishing a cuttings bed height risk matrix as described above, the abscissa may be the change rate of the hook load, the ordinate may be the deflection degree of the cuttings particle size distribution, and a size of the matrix may be determined by the percentage of returned cuttings. As the percentage of returned cuttings is reduced, the size of the matrix is increasingly reduced toward an upper right direction (as shown in FIG. 6). A reduction ratio is as follows

$\begin{array}{cc}\mu =\frac{a_1}{0.8}\times 100\%& \left(13\right)\end{array}$

• • where μ is the reduction ratio; α₁ is a percentage of actually returned cuttings.

In specific implementation, after the cuttings bed height risk level in each well section is determined based on the percentage of the drilled returned cuttings, the deflection degree of drilled cuttings particle size distribution, and the change rate of the drilling hook load in the drilling process, different cuttings bed height risk levels are associated with different cuttings bed removal solutions.

In an embodiment, the associating different cuttings bed height risk levels with different cuttings bed removal solutions includes:

• • associating a low cuttings bed height risk level with a cuttings bed removal solution in which a drilling liquid discharge is increased;
  • associating a medium cuttings bed height risk level with a cuttings bed removal solution in which the drilling liquid discharge and a turntable rotational speed are increased;
  • associating a high cuttings bed height risk level with a cuttings bed removal solution for reverse sliding into the wellbore; and
  • associating an emergent cuttings bed height risk level with a cuttings bed removal solution in which a rheological property of the drilling liquid is adjusted.

In an embodiment, the dividing the cuttings bed height risk matrix, and determining the cuttings bed height risk level associated with each divided cuttings bed height risk matrix may be specifically:

the cuttings bed height risk matrix is divided into four parts, and boundary lines of the four parts are 0.4, 1, and 1.6. In actual application, in case of four risks, the cuttings bed removal solution in which a drilling liquid discharge is increased, the cuttings bed removal solution in which the drilling liquid discharge and a turntable rotational speed are increased, the cuttings bed removal solution for reverse sliding into the wellbore, and the cuttings bed removal solution in which a rheological property of the drilling liquid is adjusted may be used sequentially.

In specific implementation, after different cuttings bed height risk levels are associated with different cuttings bed removal solutions, for each well section, the correction data of the running position of the cuttings cleaning tool for the well section and a cuttings bed removal solution associated with the cuttings bed height risk level for the well section are output.

In the embodiment of the present disclosure, predicting a distribution pattern of a cuttings bed throughout a drilling process based on drilling engineering information of a horizontal well, where the distribution pattern of the cuttings bed throughout the drilling process is used for describing the predicted cuttings accumulation and remove of the cuttings bed in each well section; predicting a running position of a cuttings cleaning tool for each well section based on the distribution pattern of the cuttings bed throughout the drilling process; calculating an actual cuttings bed height in each well section based on logging data during the drilling process; correcting the predicted running position of the cuttings cleaning tool for each well section based on the actual cuttings bed height in each well section, to obtain correction data of the running position of the cuttings cleaning tool for each well section; determining a cuttings bed height risk level in each well section based on a percentage of drilled returned cuttings, a deflection degree of drilled cuttings particle size distribution, and a change rate of a drilling hook load in the drilling process; associating different cuttings bed height risk levels with different cuttings bed removal solutions; and for each well section, outputting the correction data of the running position of the cuttings cleaning tool for the well section and a cuttings bed removal solution associated with the cuttings bed height risk level for the well section. Compared with the technical solution in which only a conventional cleaning manner can be manually formulated in the prior art, the distribution pattern of the cuttings bed throughout the drilling process is predicted, and different cuttings bed removal solutions are carried out for different cuttings bed height risk levels, so that the cuttings bed in the horizontal well is processed by integrating pre-drilling simulation prediction, drilling diagnosis and evaluation, and cuttings removal operation guidance, without the help of manpower anymore, the running position of the cuttings cleaning tool can be automatically adjusted, and a cuttings bed cleaning solution is automatically generated. Therefore, a problem that mistakes and omissions cannot be avoided in manual work in the prior art is resolved, the accuracy and the efficiency of the cuttings bed processing in the horizontal well are improved, the problem of accumulation of the cuttings bed in the horizontal well is effectively resolved, and a development benefit of the horizontal well is improved.

As described above, an embodiment of the present disclosure provides an integrated solution for predicting, monitoring, and clearing cuttings beds in horizontal wells, which can be used for accurately predicting the cuttings bed height before drilling, formulating a cuttings removal solution, connecting logger information during drilling, analyzing the cuttings bed height in real time, optimizing and combining cuttings removal manners, and resolving a problem of accumulation of the cuttings bed in the horizontal well.

An embodiment of the present disclosure further provides a device for horizontal well cuttings bed processing, as described in the following embodiment. Because a principle for the device to resolve a problem is similar to the method for resolving the cuttings bed in the horizontal well, for implementation of the device, reference may be made to the implementation of the method for processing the cuttings bed in the horizontal well, which are not repeated herein again.

An embodiment of the present disclosure provides a device for horizontal well cuttings bed processing, to improve processing accuracy and processing efficiency of the cuttings bed in a horizontal well, effectively resolving a problem of accumulation of the cuttings bed in a horizontal well, and improving the development benefit of the horizontal well. Refer to FIG. 2, the device includes:

• • a cuttings bed distribution pattern prediction module 201, configured to predict a distribution pattern of a cuttings bed throughout a drilling process based on drilling engineering information of a horizontal well, where the distribution pattern of the cuttings bed throughout the drilling process is used for describing predicted cuttings accumulation and remove of the cuttings bed in each well section;
  • a cuttings cleaning tool running position prediction module 202, configured to predict a running position of a cuttings cleaning tool for each well section based on the distribution pattern of the cuttings bed throughout the drilling process;
  • an actual cuttings bed height calculation module 203, configured to calculate an actual cuttings bed height in each well section based on logging data during the drilling process;
  • a cuttings cleaning tool running position correction module 204, configured to correct the predicted running position of the cuttings cleaning tool for each well section based on the actual cuttings bed height in each well section, to obtain correction data of the running position of the cuttings cleaning tool for each well section;
  • a well-section cuttings bed height risk level determining module 205, configured to determine the cuttings bed height risk level in each well section based on a percentage of the drilled returned cuttings, a deflection degree of drilled cuttings particle size distribution, and a change rate of a drilling hook load in the drilling process;
  • a cuttings bed removal solution association module 206, configured to associate different cuttings bed height risk levels with different cuttings bed removal solutions; and
  • a data output module 207, configured to output, for each well section, the correction data of the running position of the cuttings cleaning tool for the well section and a cuttings bed removal solution associated with the cuttings bed height risk level for the well section.

In an embodiment, the cuttings bed distribution pattern prediction module is specifically configured to:

• • based on a finite volume method and in combination with the drilling engineering information, calculate and simulate a drilling time axis, to obtain the predicted distribution pattern of the cuttings bed throughout the drilling process.

In an embodiment, the well-section cuttings bed height risk level determining module is specifically configured to:

• • pre-establish a cuttings bed height risk matrix, where the cuttings bed height risk matrix takes a change rate of an initial drilling hook load as an abscissa, a deflection degree of initial drilled cuttings particle size distribution as an ordinate, and a percentage of initial returned cuttings as a matrix size;
  • divide the cuttings bed height risk matrix, and determining the cuttings bed height risk level associated with each divided cuttings bed height risk matrix; and
  • match the percentage of the drilled returned cuttings, the deflection degree of the drilled cuttings particle size distribution, and the change rate of the drilling hook load in the drilling process with each divided cuttings bed height risk matrix, to obtain the cuttings bed height risk level in each well section.

In an embodiment, the cuttings bed removal solution association module is specifically configured to:

• • associate a low cuttings bed height risk level with a cuttings bed removal solution in which a drilling liquid discharge is increased;
  • associate a medium cuttings bed height risk level with a cuttings bed removal solution in which the drilling liquid discharge and a turntable rotational speed are increased;
  • associate a high cuttings bed height risk level with a cuttings bed removal solution for reverse sliding into the wellbore; and
  • associate an emergent cuttings bed height risk level with a cuttings bed removal solution in which a rheological property of the drilling liquid is adjusted.

A specific embodiment is provided below to illustrate a specific application of the device of the present disclosure.

Refer to FIG. 3, FIG. 4, and FIG. 6. The embodiment provides a solution for integrated prediction, diagnosis, and removal solution of a cuttings bed in a horizontal well, which can be used for accurately predicting a cuttings bed height before drilling and formulating a cuttings removal solution. Logger information may be connected during drilling, the cuttings bed height may be analyzed in real time, cuttings removal manners are optimized and combined, and a problem of accumulation of the cuttings bed in the horizontal well is resolved.

Numerals in FIG. 3, FIG. 4, and FIG. 6 are explained as follows:

In the figures, 1 is a cuttings bed prediction module, 2 is a logger, 3 is a logger connecting device, 4 is a central processing computer, 5 is a client computer, 6 is a normal particle size distribution curve, 7 is a high cuttings-cleaning efficiency particle size distribution curve, 8 is a low cuttings-cleaning efficiency particle size distribution curve, 9 is a deflection distance, and 10 is an initial cuttings bed height risk matrix, 11 is a cuttings bed height risk matrix with 70% of cuttings returned, 12 is a sand removal low-risk region, 13 is a sand removal medium-risk region, 14 is a sand removal high-risk region, and 15 is a sand removal emergency risk region.

Refer to FIG. 3. The device in this embodiment may work in combination with the logger, the logger connecting device, the central processing computer, and the client computer, and may further form an integrated prediction, diagnosis, and removal equipment for the cuttings bed in the horizontal well, which is described in detail as follows.

Refer to FIG. 3. The integrated prediction, diagnosis, and removal equipment for the cuttings bed in the horizontal well may include the cuttings bed prediction module 1 (that is, the above cuttings bed distribution pattern prediction module and the cuttings cleaning tool running position prediction module), the logger 2, the logger connecting device 3, the central processing computer 4 (which may include the above cuttings cleaning tool running position correction module, the well-section cuttings bed height risk level determining module, the cuttings bed removal solution association module, and the data output module), and the client computer 5.

Refer to FIG. 3. The cuttings bed prediction module 1 may include a computer with a numerical calculation capability, and may calculate, in combination with drilling engineering design data (that is, the above drilling engineering information of the horizontal well, such as the well depth, the well diameter, the discharge, the drilling liquid property, the rate of penetration, the drill assembly, the well inclination angle, and the cuttings density) based on the finite volume method, the cuttings bed distribution pattern throughout the drilling process before drilling, and guide the design of the running position of the wellbore cleaning tool.

Refer to FIG. 3. For the cuttings bed prediction module 1 in the integrated prediction, diagnosis, and removal device for the cuttings bed in the horizontal well, the cuttings and the drilling liquid satisfy the mass conservation equation and momentum conservation equation:

$\begin{array}{cc}\{\begin{array}{c}\frac{\partial }{\partial t}\left[\left(1-\alpha \right){\rho }_l\right]+\frac{\partial }{\partial x}\left[\left(1-\alpha \right){\rho }_l{v}_l\right]=0\\ \frac{\partial }{\partial t}\left({\mathrm{\alpha \rho }}_s\right)+\frac{\partial }{\partial x}\left(\alpha {\rho }_s{v}_s\right)=0\\ \frac{\partial }{\partial t}\left[\left(1-\alpha \right){\rho }_l{v}_l+\alpha {\rho }_s{v}_s\right]+\frac{\partial }{\partial x}\left[\left(1-\alpha \right){\rho }_l{v}_l^2+\alpha {\rho }_s{v}_s^2+p\right]=s_m\end{array}& \left(1\right)\end{array}$

• • where α represents a volume fraction of the cuttings in the horizontal well section and is dimensionless; ρ_l represents density of the drilling liquid in kg/m3; ρ_s represents a density of the cuttings in kg/m³; ν_l represents a flow velocity of the drilling liquid in m/s; ν_s represents a flow velocity of the cuttings particles in m/s; p represents a pressure of the drilling liquid in pa; s_m represents a source item in pa;

$\frac{\partial }{\partial t}$

represents a partial derivative of a parameter with respect to time in the unit of s⁻¹;

$\frac{\partial }{\partial x}$

represents a partial derivative of a parameter with respect to space in the unit of m⁻¹.

Take intermediate variables W_l, W_s, W_p, and a matrix F, with expressions of the above Formula (2) and Formula (3) respectively.

In the calculation of the cuttings bed distribution based on the finite volume method, flux changes of conservation variables of a liquid phase, a solid phase, and a mixed momentum term satisfy the above Formula (4).

• • Step 4: After discretization, equation forms are shown in the above Formula (5)-Formula (7).
  • where subscripts i and old−i respectively represent parameter values of a i well section and a old−iwell section; superscripts j and j+1 respectively represent parameter values of well sections at a t time point and a t+Δt time point: further, old−li represents a value of an intermediate variable W_l of the liquid phase in a i well section at a j time point; old−si represents a value of an intermediate variable W_s of the solid phase in a i well section at a j time point; old−Pi represents a value of an intermediate variable W_p of a pressure in a i well section at a j time point; li represents a value of an intermediate variable W_l of the liquid phase in a i well section at a j+1 time point; si represents a value of an intermediate variable W_s of the solid phase in a i well section at a j+1 time point; and Pi represents a value of an intermediate variable W_p of a pressure in a i well section at a j+1 time point.

The liquid phase, the solid phase, and the mixed phase respectively represent a drilling liquid portion, cuttings portion, and a mixed portion of the drilling liquid and cuttings in the well section.

The flux F in each grid within a time interval At is updated, and then transverse calculation simulation is performed by using a time axis, to obtain the cuttings accumulation and remove throughout the drilling process.

Refer to FIG. 3. Real-time logging data of the logger 2 in the integrated prediction, diagnosis, and removal device for the cuttings bed in the horizontal well may include: a well depth, a drilling rate, a drilling liquid density, a pump pressure, a discharge, a wellbore structure, a well trajectory, a drill assembly, a percentage of returned cuttings, and cuttings particle size distribution.

Refer to FIG. 3. The logger 2 in the integrated prediction, diagnosis, and removal device for the cuttings bed in the horizontal well may transmit collected data to the central processing computer 4 in real time by using the logger connecting device 3, for computation.

Refer to FIG. 3, FIG. 4, and FIG. 6. Real-time monitoring of the cuttings bed height in the integrated prediction, diagnosis, and removal device for the cuttings bed in the horizontal well may include three parts: the percentage of returned cuttings, cuttings particle size distribution of the solid phase of the drilling liquid, and the change rate of the hook load.

Refer to FIG. 3. The percentage of the returned cuttings may be defined as a ratio of the mass of the cuttings generated by drilling to the mass of a wellhead returned cuttings. The percentage of the returned cuttings that reaches 80% can be defined as a safe drilling sign, and no additional sand cleaning operation is needed during drilling.

$\begin{array}{cc}{M}_{sum}={\int }_{t_0}^{t_1}\mathrm{vt}{\rho }_{\mathrm{cuttings}}\frac{\pi D^2}{4}\mathrm{dt}& \left(8\right)\end{array}$ $\begin{array}{cc}\alpha =\frac{M_{real}}{M_{sum}}\times 100\%& \left(9\right)\end{array}$

where M_sum is a total amount of the cuttings generated by drilling in Δt time; v is the drilling rate; t is time; ρ_cuttings is a density of the cuttings at this time (related to a stratum drilled in the well); D is a diameter of a bit; α is the percentage of the returned cuttings; and M_real is an amount of return cuttings in the well in the Δt time.

Refer to FIG. 4. A triaxial average diameter is used as the diameter of the cuttings particles in the cuttings particle size distribution diagram, and the distribution graph of the cuttings particle size of the solid phase of the drilling liquid presents normal distribution 6 in a normal drilling process. When a cuttings cleaning degree is relatively low, the distribution graph of the cuttings particle size is in a left deflection form 8. When the a cuttings cleaning degree is relatively high, the distribution graph of the cuttings particle size is in a right deflection form 7.

Refer to FIG. 4. In the cuttings particle size distribution graph, the deflection degree is used to characterize the cuttings cleaning effect. The deflection degree is defined as a ratio of the deflection distance 9 to a span of a cuttings particle diameter. As a degree of the left deflection 8 is higher, cuttings cleaning efficiency is lower. As a degree of the right deflection 7 is higher, cuttings cleaning efficiency is higher.

$\begin{array}{cc}\beta =\frac{L}{d_2-d_1}\times 100\%& \left(10\right)\end{array}$

• • where β is the deflection degree; L is a deflection distance; d₂ is a maximum diameter of the cuttings particles; and d₁ is a smallest diameter of the cuttings particles.

Refer to FIG. 3. The hook load change is derived from an increase in small solid particles during drilling, which is caused by repeated breaking of the cuttings. As a change rate of the hook load is greater, the cuttings cleaning effect is low.

$\begin{array}{cc}{G}_1=Mg-{\rho }_1\mathrm{gV}& \left(11\right)\end{array}$ $\begin{array}{cc}\eta =\frac{G_{real}}{G_1}\times 100\%& \left(12\right)\end{array}$

• • where η is the change rate of the hook load; G₁ is a theoretical load; M is a total mass of the drill; ρ₁ is a density of the drilling liquid; V is a total volume of the drill; and G_real is an actual load.

Refer to FIG. 6. The abscissa may be the change rate of the hook load, the ordinate may be the deflection degree of the cuttings particle size distribution, and a size of the matrix may be determined by the percentage of returned cuttings, and the cuttings bed height risk matrix 11 is built. As the percentage of returned cuttings is reduced, the size of the matrix is increasingly reduced toward an upper right direction. The cuttings bed height risk matrix 11 with 70% of cuttings returned is reduced at the following ratio

$\begin{array}{cc}\mu =\frac{a_1}{0.8}\times 100\%& \left(13\right)\end{array}$

• • where μ is the reduction ratio; α₁ is a percentage of actually returned cuttings.

Refer to FIG. 7. The cuttings bed height risk matrix in an embodiment of the present disclosure may be built based on the risk level classification method proposed in API 581 Base Resource Document-Risk Based Inspection of the American Petroleum Institute (API). In the example, a risk of an event sequence may be defined as A=a·X+b·Y, where a=0.4 and b=0.6. A boundary line is a value A. In the embodiment of the present disclosure, the cuttings bed height risk matrix is divided based on a value obtained through massive engineering practices, and this value may be freely set by the staff based on an actual drilling condition.

Refer to FIG. 6. The cuttings bed height risk matrix may be divided into four parts, and boundary lines of the four parts are 0.4, 1, and 1.6. Confronted with different risks, in the sand removal low-risk region (that is, the above low cuttings bed height risk level region) 12, a selected sand removal manner is increase of the drilling liquid discharge. In the sand removal medium-risk region (that is, the above medium cuttings bed height risk level region) 13, a selected sand removal manner is increase of the drilling liquid discharge and the turntable rotational speed. In the sand removal high-risk region (that is, the above high cuttings bed height risk level region) 14, a selected sand removal manner is the reverse sliding into the wellbore. In the sand removal emergency risk region (that is, the above emergency cuttings bed height risk level region) 15, a selected sand removal manner is adjustment of rheological property and increase of a cuttings carrying capability of the drilling liquid.

Refer to FIG. 6. The left picture and the right picture are compared. The area of the sand removal low-risk region on the lower left is reduced, the area of the sand removal medium-risk region is reduced, the sand removal high-risk region is changed into a hexagon region, and the area of the sand removal emergency risk region keeps unchanged. The reason is that a coordinate axis generally moves to the upper right. As the percentage of returned cuttings becomes lower, only small changes in load weight and cuttings deflection are required to achieve a same sand removal risk.

Refer to FIG. 3. The central processing computer 4 performs real-time assessment of the cuttings bed height and drilling risk, and compares the assessed cuttings bed height and drilling risk with a predicted cuttings bed height curve, to optimize the running position of the cuttings cleaning tool.

Refer to FIG. 3. In the integrated prediction, diagnosis, and removal device for the cuttings bed in the horizontal well, risk matrix calculation is all completed in the central processing computer 4, and design of a cuttings cleaning solution is completed. A cuttings processing solution generated by the central processing computer 4 is transmitted to the client computer 5, to guide an on-site cuttings cleaning operation.

A supporting solution for integrated prediction, diagnosis, and removal of the cuttings bed in a horizontal well is as follows:

• • 1. a computer inputs the drilling engineering information, calculates the distribution pattern of the cuttings bed in the whole well section, designs the running position of the cuttings cleaning tool, and transmits the information, the distribution pattern, and the running position to the central processing computer;
  • 2. the logger is connected to the central processing computer, to perform real-time cuttings bed risk assessment, specify the sand cleaning solution, and compare the sand removal solution with the predicted cuttings bed distribution, and optimize the running position of the cuttings cleaning tool; and
  • 3. the central processing computer transmits the formulated cuttings removal solution and the tool running solution to the client computer in real time, and a construction solution for the drilling site tool is used for the sand cleaning operation.

In the above embodiment, the solution for integrated prediction, diagnosis, and removal of a cuttings bed in a horizontal well solution is implemented. The solution has the following greatest advantage: pre-drilling simulation and prediction, drilling diagnostic assessment, cuttings cleaning operation tool, and the cuttings cleaning operation guidance are integrated to resolve the problem of cuttings remove in the horizontal well section, and reduce a drilling risk caused by cuttings bed accumulation during horizontal well drilling. Cuttings bed prediction is used to accurately predict the height and location of the cuttings bed before drilling, and to design the layout of the cuttings cleaning tool in a cuttings deposition section. The logger connecting device collects and transmits data in real time, and the central processing computer calculates and analyzes the distribution pattern of the cuttings bed in real time and outputs the distribution pattern to the client computer, so that a calculation result is output in real time. A friction torque and drill sticking risk are reduced in the horizontal section, the rate of penetration is increased, and the development efficiency of the horizontal well is further improved.

Of course, it can be understood that other variation examples may also be provided for the above detailed modules, and the relevant variation examples shall fall within the protection scope of the present disclosure.

Based on the above inventive concept, as shown in FIG. 5, the present disclosure further provides a computer equipment 500, including a memory 510, a processor 520, and a computer program 530 stored on the memory 510 and runnable on the processor 520. When the processor 520 executes the computer program 530, the above method for horizontal well cuttings bed processing is performed.

An embodiment of the present disclosure further provides a computer-readable storage medium. The computer-readable storage medium stores a computer program. When the computer program is executed by a processor, the above method for horizontal well cuttings bed processing is implemented.

An embodiment of the present disclosure further provides a computer program product. The computer program product includes a computer program. When the computer program is executed by a processor, the above method for horizontal well cuttings bed processing is implemented.

In the embodiment of the present disclosure, predicting a distribution pattern of a cuttings bed throughout a drilling process based on drilling engineering information of a horizontal well, where the distribution pattern of the cuttings bed throughout the drilling process is used for describing the predicted cuttings accumulation and remove of the cuttings bed in each well section; predicting a running position of a cuttings cleaning tool for each well section based on the distribution pattern of the cuttings bed throughout the drilling process; calculating an actual cuttings bed height in each well section based on logging data in the drilling process; correcting the predicted running position of the cuttings cleaning tool for each well section based on the actual cuttings bed height in each well section, to obtain correction data of the running position of the cuttings cleaning tool for each well section; determining a cuttings bed height risk level in each well section based on a percentage of drilled returned cuttings, a deflection degree of drilled cuttings particle size distribution, and a change rate of a drilling hook load in the drilling process; associating different cuttings bed height risk levels with different cuttings bed removal solutions; and for each well section, outputting the correction data of the running position of the cuttings cleaning tool for the well section and a cuttings bed removal solution associated with the cuttings bed height risk level for the well section. Compared with the technical solution in which only a conventional cleaning manner can be manually formulated in the prior art, the distribution pattern of the cuttings bed throughout the drilling process is predicted, and different cuttings bed removal solutions are carried out for different cuttings bed height risk levels, so that cuttings bed in a horizontal well is processed by integrating pre-drilling simulation prediction, drilling diagnosis and evaluation, and cuttings removal operation guidance, without the help of manpower, the running position of the cuttings cleaning tool can be automatically adjusted, and a cuttings bed cleaning solution is generated. Therefore, a problem that mistakes and omissions cannot be avoided in manual work in the prior art is resolved, the processing accuracy and the processing efficiency of the cuttings bed in the horizontal well are improved, the problem of accumulation of the cuttings bed in a horizontal well is effectively resolved, and a development benefit of the horizontal well is improved.

A person skilled in the art should understand that the embodiments of the present disclosure can be provided as a method, a system, or a computer program product. Therefore, the present disclosure may use a form of hardware only embodiments, software only embodiments, or embodiments with a combination of software and hardware. Moreover, the present disclosure may use a form of a computer program product that is implemented on one or more computer-usable storage media (including but not limited to a magnetic disk memory, a CD-ROM, an optical memory, and the like) that include a computer-usable program code.

The present disclosure is described with reference to the flowcharts and/or block diagrams of the methods, equipment (systems), and computer program products according to the embodiments of the present disclosure. It should be understood that each process and/or block in the flowchart and/or block diagram as well as a combination of processes and/or blocks in the flowchart and/or block diagram may be implemented by computer program instructions. These computer program instructions can be provided to a general-purpose computer, a special-purpose computer, an embedded processor, or a processor of another programmable data processing equipment to generate a machine, so that a device configured to implement functions specified in one or more procedures of a flowchart and/or one or more blocks of a block diagram is generated by using the instructions executed by the computer or the processor of the another programmable data processing equipment.

These computer program instructions may also be stored in a computer readable memory that can instruct the computer or any other programmable data processing equipment to work in a specific manner, so that the instructions stored in the computer readable memory generate an artifact that includes an instruction device. The instruction device implements a function specified in one or more procedures of the flowchart and/or in one or more blocks of the block diagram.

These computer program instructions may also be loaded onto a computer or another programmable data processing equipment, so that a series of operation steps are performed on the computer or another programmable equipment to produce computer-implemented processing, thereby providing instructions executed on the computer or another programmable equipment to implement steps for the function specified in one or more processes of the flowchart and/or one or more blocks of the block diagram.

In the above specific embodiments, the objectives, technical solutions, and beneficial effects of the present disclosure are further described in detail. It should be understood that the above descriptions are merely specific embodiments of the present disclosure, but are not intended to limit the protection scope of the present disclosure. Any modification, equivalent replacement, improvement, or the like made without departing from the spirit and principle of the present disclosure shall fall within the protection scope of the present disclosure.

Claims

1. A horizontal well cuttings bed processing method, comprising: predicting a distribution pattern of the cuttings bed throughout a drilling process based on drilling engineering information of the horizontal well, wherein the distribution pattern of the cuttings bed throughout the drilling process is used for describing predicted cuttings accumulation and remove of the cuttings bed in each well section;predicting a running position of a cuttings cleaning tool for each well section based on the distribution pattern of the cuttings bed throughout the drilling process;calculating an actual cuttings bed height in each well section based on logging data during the drilling process;correcting the predicted running position of the cuttings cleaning tool for each well section based on the actual cuttings bed height in each well section, to obtain correction data of the running position of the cuttings cleaning tool for each well section;determining a cuttings bed height risk level in each well section based on a percentage of drilled returned cuttings, a deflection degree of drilled cuttings particle size distribution, and a change rate of a drilling hook load in the drilling process;associating different cuttings bed height risk levels with different cuttings bed removal solutions; andfor each well section, outputting the correction data of the running position of the cuttings cleaning tool for the well section and a cuttings bed removal solution associated with the cuttings bed height risk level for the well section.

2. The method according to claim 1, wherein the predicting a distribution pattern of the cuttings bed throughout a drilling process based on drilling engineering information of the horizontal well comprises: based on a finite volume method and in combination with the drilling engineering information, calculating and simulating a drilling time axis, to obtain the predicted distribution pattern of the cuttings bed throughout the drilling process.

3. The method according to claim 1, wherein the predicting a running position of a cuttings cleaning tool for each well section based on the distribution pattern of the cuttings bed throughout the drilling process comprises: performing arrangement of the cuttings cleaning tool for cuttings deposition in key well sections based on the distribution pattern of the cuttings bed throughout the drilling process predicted before drilling, and predicting the running position of the cuttings cleaning tool for each well section.

4. The method according to claim 1, wherein the logging data comprises: one or any combination of a well depth, a drilling rate, a drilling liquid density, a pump pressure, a discharge, a wellbore structure, a well trajectory, a drill assembly, a percentage of returned cuttings, cuttings particle size distribution, and a hook load change.

5. The method according to claim 1, wherein the determining a cuttings bed height risk level in each well section based on a percentage of drilled returned cuttings, a deflection degree of drilled cuttings particle size distribution, and a change rate of a drilling hook load in the drilling process comprises: pre-establishing a cuttings bed height risk matrix, wherein the cuttings bed height risk matrix takes an initial change rate of a drilling hook load as an abscissa, an initial deflection degree of drilled cuttings particle size distribution as an ordinate, and an initial percentage of returned cuttings as a matrix size;dividing the cuttings bed height risk matrix, and determining the cuttings bed height risk level associated with each divided cuttings bed height risk matrix; andmatching the percentage of the drilled returned cuttings, the deflection degree of the drilled cuttings particle size distribution, and the change rate of the drilling hook load in the drilling process with each divided cuttings bed height risk matrix, to obtain the cuttings bed height risk level in each well section.

6. The method according to claim 1, wherein the associating different cuttings bed height risk levels with different cuttings bed removal solutions comprises: associating a low cuttings bed height risk level with a cuttings bed removal solution in which a drilling liquid discharge is increased;associating a medium cuttings bed height risk level with a cuttings bed removal solution in which the drilling liquid discharge and a turntable rotational speed are increased;associating a high cuttings bed height risk level with a cuttings bed removal solution for reverse sliding into the wellbore; andassociating an emergent cuttings bed height risk level with a cuttings bed removal solution in which a rheological property of the drilling liquid is adjusted.

7. A computer equipment, comprising a memory, a processor, and a computer program stored in the memory and runnable on the processor, wherein when the processor executes the computer program, the method according to claim 1 is implemented.

8. A computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to claim 1 is implemented.