Maintaining Wellbore Stability during Production

Abstract

Example computer-implemented methods and systems for maintaining wellbore stability during production are disclosed. One example computer-implemented method includes obtaining in-situ stress data, pore pressure data, and formation property data associated with a wellbore. One or more production rates for the wellbore are determined based on the obtained in-situ stress data, pore pressure data, and formation property data, where the wellbore maintains stability when performing a respective production operation at each of the one or more production rates. The determined one or more production rates are provided to control a production rate of the wellbore at a well head of the wellbore, where the production rate of the wellbore at the well head of the wellbore is within a range determined by the one or more production rates.

Description

TECHNICAL FIELD

The present disclosure relates to computer-implemented methods and systems for maintaining wellbore stability during production.

BACKGROUND

Wellbore stability is the ability of a wellbore to maintain its shape and size without collapsing, fracturing, or caving in due to the stresses and pressures in the subsurface. Wellbore stability is of primary importance during drilling and production of oil and gas wells, as wellbore instability can lead to significant operational and economic losses. Maintaining wellbore stability during the production operation of a wellbore is a challenging issue as many factors can affect wellbore stability of a wellbore under production.

SUMMARY

The present disclosure involves computer-implemented methods and systems for maintaining wellbore stability during production. One example computer-implemented method includes obtaining in-situ stress data, pore pressure data, and formation property data associated with a wellbore. One or more production rates for the wellbore are determined based on the obtained in-situ stress data, pore pressure data, and formation property data, where the wellbore maintains stability when performing a respective production operation at each of the one or more production rates. The determined one or more production rates are provided to control a production rate of the wellbore at a well head of the wellbore, where the production rate of the wellbore at the well head of the wellbore is within a range determined by the one or more production rates.

The previously described implementation is implementable using a computer-implemented method; a non-transitory, computer-readable medium storing computer-readable instructions to perform the computer-implemented method; and a computer system including a computer memory interoperably coupled with a hardware processor configured to perform the computer-implemented method or the instructions stored on the non-transitory, computer-readable medium. These and other embodiments may each optionally include one or more of the following features.

In some implementations, the formation property data includes at least one of Young's modulus, Poisson's ratio, rock strength, Biot's coefficient, Skempton's coefficient, or permeability associated with the wellbore.

In some implementations, obtaining the in-situ stress data, the pore pressure data, and the formation property data includes obtaining the in-situ stress data, the pore pressure data, and the formation property data from offset wells data, well tests, laboratory measurements, or well log analysis associated with the wellbore.

In some implementations, determining the one or more production rates includes determining, at the production rate of the wellbore, a shear failure potential around the wellbore based on a shear failure criterion.

In some implementations, the shear failure criterion includes a Mohr Coulomb criterion.

In some implementations, determining the one or more production rates includes determining, at the production rate of the wellbore, a failure zone having the highest shear failure potential among a plurality of zones around the wellbore, and determining the one or more production rates for the determined failure zone.

In some implementations, determining the one or more production rates for the determined failure zone includes determining the one or more production rates for the determined failure zone based on constitutive equations for a poroelastic porous medium.

In some implementations, providing the determined one or more production rates to control the production rate of the wellbore includes determine the largest production rate among the determined one or more production rates, and providing the largest production rate to control the production rate of the wellbore.

While generally described as computer-implemented software embodied on tangible media that processes and transforms the respective data, some or all of the aspects may be computer-implemented methods or further included in respective systems or other devices for performing this described functionality. The details of these and other aspects and implementations of the present disclosure are set forth in the accompanying drawings and the description below. Other features, objects, and advantages of the disclosure will be apparent from the description and drawings, and from the claims.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 illustrates wellbore instability during a production operation of a wellbore, according to some implementations.

FIG. 2 illustrates an example process of increasing a production rate of a wellbore while maintaining wellbore stability during the production operation of the wellbore, according to some implementations.

FIG. 3 illustrates an example of using well log analysis to obtain in-situ stress, pore pressure, rock's Young's modulus, Poisson's ratio, and rock strength, according to some implementations.

FIG. 4 illustrates an example distribution of pore pressure around a wellbore, according to some implementations.

FIG. 5 illustrates an example distribution of effective tangential stress around a wellbore, according to some implementations.

FIG. 6 illustrates an example contour of shear failure potential around a wellbore, according to some implementations.

FIG. 7 illustrates an example of shear failure potential at multiple production rates, according to some implementations.

FIG. 8 illustrates an example process of maximizing production rate of a wellbore while maintaining wellbore stability, according to some implementations.

FIG. 9 is a block diagram of an example computer system that can be used to provide computational functionalities associated with described algorithms, methods, functions, processes, flows, and procedures, according to some implementations of the present disclosure.

FIG. 10 illustrates hydrocarbon production operations that include both one or more field operations and one or more computational operations, which exchange information and control exploration for the production of hydrocarbons, according to some implementations.

Like reference numbers and designations in the various drawings indicate like elements.

DETAILED DESCRIPTION

This disclosure relates to systems and methods for increasing, e.g., maximizing, production rate of a wellbore while maintaining wellbore stability during production of the wellbore. Wellbore instability during production can cause significant issues. For example, the collapse of a wellbore under production can produce sands, damage production pipes, and reduce production rate. FIG. 1 illustrates wellbore instability during a production operation of a wellbore. The collapse of wellbore 102 at location 104 during production can cause damage to equipment, loss of oil or gas supply, and pose a potential threat to workers near the wellbore.

To maximize production rate of a wellbore while maintaining wellbore stability during the production operation of the wellbore, a computer system can first identify, at a specific production rate of the wellbore, a failure zone having the highest shear failure potential among all the zones around the wellbore. The computer system can then determine one or more production rates at which wellbore stability is maintained for the identified failure zone. In one example, the highest production rate among the one or more determined production rates can be used to control the production rate at the well head of the wellbore.

The disclosed systems and methods provide many advantages over existing oil and gas production systems that experience wellbore stability issues. In some cases, the disclosed systems and methods can maximize wellbore production rate while maintaining wellbore stability during the production operation of the wellbore. Additionally, the disclosed methods and systems can avoid damage to equipment as well as loss of oil and gas supply caused by wellbore instability during production.

FIG. 2 illustrates an example process 200 of increasing a production rate of a wellbore while maintaining wellbore stability during a production operation of the wellbore. For convenience, process 200 will be described as being performed by a system of one or more computers, located in one or more locations, and programmed appropriately in accordance with this specification.

At 202, a computer system obtains in-situ stress data, pore pressure data, and formation property data associated with a wellbore that is to be used for production. In some examples, the formation property data can include one or more of Young's modulus, Poisson's ratio, rock strength, Biot's coefficient, Skempton's coefficient, and/or permeability associated with the wellbore. The in-situ stress data, pore pressure data, and formation property data can be obtained from offset wells data, well test, laboratory measurements, or well log analysis. FIG. 3 illustrates an example of using well log analysis to obtain in-situ stress, pore pressure, rock's Young's modulus, Poisson's ratio, and rock strength. Table 1 below shows example values of data associated with in-situ stress data, pore pressure data, and formation property data of a wellbore.

TABLE 1
Parameters                       Values
Wellbore radius, R, (m)          0.1
Inclination angle, (°)           90
Azimuth, (°)                     90
Overburden stress gradient, (kPa/m) 29
Maximum horizontal stress gradient, (kPa/m) 25
Minimum horizontal stress gradient, (kPa/m) 20
Pore pressure gradient, (kPa/m)  9.8
Flow rate, (m3/hr)               0.18
Young's modulus, (GPa)           6
Poisson' ratio, dimensionless    0.22
Permeability, (mD)               0.0001
Biot's coefficient, dimensionless 1
Skempton's coefficient, dimensionless 0.9
Fluid viscosity, (cP)            1

Returning to FIG. 2, at 204, the computer system determines, using the data obtained at 202, the wellbore stress and the pore pressure around the wellbore, at a specific production rate of the wellbore.

In some implementations, a set of equations that are based on the theory of poroelasticity can be used to determine the wellbore stresses and pore pressure around the wellbore, using data obtained at 202 as inputs to the set of equations.

For example, the constitutive equations for a poroelastic porous medium are shown in Equations 1-5.

$\begin{array}{cc}{\sigma }_{\mathrm{rr}}=\frac{E}{1+v}\left({\epsilon }_{\mathrm{rr}}+\frac{v}{1-2v}{\epsilon }_{\mathrm{kk}}\right)+\alpha p& \left(1\right)\end{array}$ $\begin{array}{cc}{\sigma }_{\theta \theta }=\frac{E}{1+v}\left({\epsilon }_{\theta \theta }+\frac{v}{1-2v}{\epsilon }_{\mathrm{kk}}\right)+\alpha p& \left(2\right)\end{array}$ $\begin{array}{cc}{\sigma }_{\mathrm{zz}}=\frac{E}{1+v}\left({\epsilon }_{\mathrm{zz}}+\frac{v}{1-2v}{\epsilon }_{\mathrm{kk}}\right)+\alpha p& \left(3\right)\end{array}$ $\begin{array}{cc}{\sigma }_{r\theta }=\frac{E}{1+v}{\epsilon }_{r\theta }+\alpha p& \left(4\right)\end{array}$ $\begin{array}{cc}\zeta =-\alpha {\epsilon }_{\mathrm{kk}}+\frac{p}{M}.& \left(5\right)\end{array}$

In these Equations, σ_ij and ε_ij are the stress and strain tensors, ε_kk is the volumetric strain, E and ν are the Young's modulus and Poisson's ratio, α is Biot's coefficient, p is the pore pressure, ξ is the variation of fluid content, and M is Biot's modulus.

The mass balance equation for the fluid flow in the pore spaces is shown in Equation 6.

$\begin{array}{cc}\frac{\partial \zeta }{\partial t}=-\nabla q& \left(6\right)\end{array}$

In Equation 6, t is the time and q is the fluid flux. The strain-displacement relations and equilibrium equations are shown in Equations 7 and 8 respectively.

$\begin{array}{cc}{\epsilon }_{\mathrm{ij}}=\frac{1}{2}\left(\frac{\partial u_i}{\partial x_j}+\frac{\partial u_j}{\partial x_i}\right)& \left(7\right)\end{array}$ $\begin{array}{cc}\frac{\partial {\sigma }_{\mathrm{ij}}}{\partial x_j}=0& \left(8\right)\end{array}$

In these Equations, p is the pore pressure, σ_rr, σ_θθ, and σ_zz are the radial, tangential, and axial stresses, respectively.

The fluid flow in the porous medium can be modeled based on Darcy's law, as shown in Equation 9.

$\begin{array}{cc}q=-\frac{k}{\mu }\nabla p\#& \left(9\right)\end{array}$

In some implementations, the boundary conditions for a wellbore under production are shown in Equations 10-13.

$\begin{array}{cc}\mathrm{At}r\to \infty :{\sigma }_{\mathrm{xx}}=S_x;{\sigma }_{\mathrm{yy}}=S_y;{\sigma }_{zz}=S_z& \left(10\right)\end{array}$ $\begin{array}{cc}{\sigma }_{\mathrm{xy}}=S_{\mathrm{xy}};{\sigma }_{\mathrm{yz}}=S_{\mathrm{yz}};{\sigma }_{\mathrm{xz}}=S_{\mathrm{xz}}& \left(11\right)\end{array}$ $\begin{array}{cc}p=p_0& \left(12\right)\end{array}$ $\begin{array}{cc}\mathrm{At}r=R:{\sigma }_{\mathrm{rr}}=p_w;{\sigma }_{r\theta }=0;{\sigma }_{\mathrm{rz}}=0;q=q_w& \left(13\right)\end{array}$

In these Equations, S_x, S_y, S_z, S_xy, S_yz, and S_xz are the far-field stresses, p₀ is the in-situ pore pressure, q_w is the production rate from the wellbore. The initial conditions at t=0 can be described by Equations 10-12. In other words, at t=0, the stresses and pore pressure are the same as the far-field values.

In some implementations, the analytical solutions of the stress and pore pressure around a wellbore under production are shown in Equations 14-20.

$\begin{array}{cc}p={\mathrm{gC}}_1+C_2{K}_0\left(\frac{\xi r}{R}\right)+{\mathrm{gD}}_1{r}^{-2}+D_2{K}_2\left(\frac{\xi r}{R}\right)& \left(14\right)\end{array}$ $\begin{array}{cc}{\sigma }_{\mathrm{rr}}=C_0{r}^{-2}+A_1{C}_1-A_2{C}_2\frac{K_{-1}\left(\frac{\xi r}{R}\right)}{\xi r}+\left\{D_0{r}^{-4}+2A_1{D}_1{r}^{-2}-A_2{D}_2\left[\frac{K_1\left(\xi r\right)}{\xi r}+\frac{6K_2\left(\xi r\right)}{{\xi }^2{r}^2}\right]\right\}\cos 2\left(\theta -{\theta }_r\right)& \left(15\right)\end{array}$ $\begin{array}{cc}{\sigma }_{\theta \theta }=-C_0{r}^{-2}+A_1{C}_1+A_2{C}_2\left[\frac{K_{-1}\left(\frac{\xi r}{R}\right)}{\xi r}+K_0\left(\frac{\xi r}{R}\right)\right]+\left\{-D_0{r}^{-4}+A_2{D}_2\left[\frac{K_1\left(\xi r\right)}{\xi r}+\left(1+\frac{6}{{\xi }^2{r}^2}\right)K_2\left(\xi r\right)\right]\right\}\cos 2\left(\theta -{\theta }_r\right)& \left(16\right)\end{array}$ $\begin{array}{cc}{\sigma }_{\mathrm{zz}}=S_z-v\left(S_x+S_y\right)+v\left({\sigma }_{\mathrm{rr}}+{\sigma }_{\theta \theta }\right)+\left(1-2v\right)\alpha \left(p-p_0\right)& \left(17\right)\end{array}$ $\begin{array}{cc}{\sigma }_{r\theta }=C_0{r}^{-2}\left\{+D_0{r}^{-4}+A_1{D}_1{r}^{-2}-A_2{D}_2\left[\frac{2K_1\left(\zeta r\right)}{\xi r}+\frac{6}{{\zeta }^2{r}^2}{K}_2\left(\xi r\right)\right]\right\}\sin 2\left(\theta -{\theta }_r\right)& \left(18\right)\end{array}$ $\begin{array}{cc}{\sigma }_{\mathrm{rz}}=\left(S_{\mathrm{xz}}\cos \theta +S_{\mathrm{yz}}\sin \theta \right)\left(1-\frac{R^2}{r^2}\right)& \left(19\right)\end{array}$ $\begin{array}{cc}{\sigma }_{\theta z}=-\left(S_{\mathrm{xz}}\sin \theta -S_{\mathrm{yz}}\cos \theta \right)\left(1+\frac{R^2}{r^2}\right)& \left(20\right)\end{array}$

In these Equations, θ_r is the direction of the in-plane maximum principal stress, θ is the wellbore angle, ξ is a parameter dependent on rock properties, C_i and D_i are solution parameters depending on the boundary conditions including the production rate and far-field stresses and pore pressure. K_i(x) is the modified Bessel function of the second kind with order i. In some cases, g, A_i, ξ, C_i, and D_i can be defined by Equations 21-30.

$\begin{array}{cc}g=\frac{\alpha \left(1+v\right)\left(1-2v\right)}{E\left(1-v\right)}& \left(21\right)\end{array}$ $\begin{array}{cc}{A}_1=\frac{R^2}{1-v}& \left(22\right)\end{array}$ $\begin{array}{cc}{A}_2=\frac{2\alpha \left(1+v\right)\left(1-2v\right)p_0{K}_1\left(\xi \right)}{\left(1-v\right)}& \left(23\right)\end{array}$ $\begin{array}{cc}\xi =\sqrt{\frac{\mu }{k}\left(\frac{{\alpha }^2\left(1+v\right)\left(1-2v\right)}{E\left(1-v\right)}+\frac{1}{M}\right)}& \left(24\right)\end{array}$ $\begin{array}{cc}{C}_0=\frac{2p_0{R}^2{K}_1\left(\xi \right)}{K_0\left(\xi \right)}& \left(25\right)\end{array}$ $\begin{array}{cc}{C}_1=p_0{R}^2& \left(26\right)\end{array}$ $\begin{array}{cc}{C}_2=\frac{2p_0{\mathrm{RK}}_1\left(\xi \right)}{K_0\left(\xi \right)}& \left(27\right)\end{array}$ $\begin{array}{cc}{D}_0=\frac{\left(S_x+S_y\right)\left(1+v\right)R^4}{2\left(1-v\right)}& \left(28\right)\end{array}$ $\begin{array}{cc}{D}_1=\frac{\left(S_x+S_y\right)\left(1+v\right)R^2}{2{\left(1-v\right)}^2}& \left(29\right)\end{array}$ $\begin{array}{cc}{D}_2=\frac{\left(S_x+S_y\right)\left(1+v\right)p_0{R}^2}{2\left(1-v\right)}& \left(30\right)\end{array}$

In Equation 21-24, u is fluid viscosity, k is formation permeability, a is Biot's coefficient, ν is Poisson's ratio, E is Young's modulus, and M is Biot's modulus. In Equations 25-30, p₀ is the initial pore pressure, S_x and S_y are far field stresses.

In some implementations, the computer system determines a shear failure criterion, for example, the Mohr Coulomb criterion shown in Equation 31.

$\begin{array}{cc}\frac{{\sigma }_1^{\prime }-{\sigma }_3^{\prime }}{2}=\frac{{\sigma }_1^{\prime }+{\sigma }_3^{\prime }}{2}\tan \varphi +c& \left(31\right)\end{array}$

In Equation 31, σ′₁ and σ′₃ are the maximum and minimum effective principal stresses, ϕ is the friction angle, and c is the cohesion.

At 206, the computer system determines the stability of the wellbore at a specific production rate, by combining the wellbore solutions determined at 204 according to Equations 14-30 with the shear failure criterion, for example, the Mohr Coulomb criterion determined at 204 according to Equation 31. Consequently, the wellbore collapse occurs if Condition 32 below is satisfied.

$\begin{array}{cc}\frac{{\Delta }_1^{\prime }-{\Delta }_3^{\prime }}{2}-\left(\frac{{\Delta }_1^{\prime }+{\Delta }_3^{\prime }}{2}\tan \varphi +c\right)>0& \left(32\right)\end{array}$

In Condition 32, Δ′₁ and Δ′₃ are the maximum and minimum eigenvalues of Matrix 33:

$\begin{array}{cc}\left[\begin{array}{ccc}{\sigma }_{\mathrm{rr}}-p& {\sigma }_{r\theta }& {\sigma }_{\mathrm{rz}}\\ {\sigma }_{r\theta }& {\sigma }_{\mathrm{\theta \theta }}-p& {\sigma }_{\mathrm{\theta z}}\\ {\sigma }_{\mathrm{rz}}& {\sigma }_{\mathrm{\theta z}}& {\sigma }_z-p\end{array}\right]& \left(33\right)\end{array}$

In some implementations, the computer system can determine, using the data obtained at 202 and the equations described at 204, the contours of pore pressure and effective tangential stress around a wellbore under production. The contours show which zone around the wellbore has the highest potential for wellbore collapse. For example, FIG. 4 illustrates an example distribution of pore pressure around a wellbore with input data shown in Table 1 and at a particular time, for example, 15 minutes since the start of the production at the wellbore. The zone with higher pore pressure is under higher compressional stress than the zone with lower pore pressure. FIG. 5 illustrates an example distribution of effective tangential stress around a wellbore. Consistent with the contour of pore pressure shown in FIG. 4, FIG. 5 shows that the zone around 0-90° (note that 0=0° corresponds to the bottom in FIG. 4) exhibits the largest compressional stress. As such, the zone around 0-90° has higher potential for shear failure than the other zones. The computer system can determine the value of shear failure potential at 0=90° in order to analyze wellbore shear failure around the wellbore.

Returning to FIG. 2, at 208, the computer system determines one or more production rates for the wellbore such that the wellbore is stable at the one or more production rates. As shown in Condition 32, the left side of Condition 32, which represents the shear failure potential, depends on the production rate of the wellbore under production. Equation 34 denotes the left side of Condition 32 as V, and consequently the wellbore is stable when V is less than or equal to zero and unstable when V is greater than zero. A plot of the value of V around the wellbore for a specific production rate can indicate the failure zone around the wellbore. For example, FIG. 6 illustrates an example contour of shear failure potential around the wellbore in the example described at 206. A zone with V greater than zero indicates that shear failure occurs. A zone with V smaller than zero indicates that the wellbore under production is stable. As shown in FIGS. 4-6, the zone with the highest shear failure potential occurs at 0-90° for the example shown.

$\begin{array}{cc}V=\frac{{\Delta }_1^{\prime }-{\Delta }_3^{\prime }}{2}-\left(\frac{{\Delta }_1^{\prime }+{\Delta }_3^{\prime }}{2}\tan \varphi +c\right)& \left(34\right)\end{array}$

In some implementations, once the failure zone is determined for a specific production rate, the computer system can determine the value of shear failure potential V as a function of the production rate, for the determined failure zone. In some examples, the computer system can plot the curve of V within a range of production rates, starting at a production rate of zero, for the determined failure zone. The computer system can then determine the critical production rate, q₀, that satisfies V(q=q₀)=0 and maintains wellbore stability. If there are multiple critical values of q₀, then each production rate that keeps the wellbore stable falls within the ranges between these critical values such that the corresponding shear failure potential V is less than zero, and consequently the wellbore is stable.

For example, FIG. 7 illustrates an example of shear failure potential at multiple production rates, starting at the production rate of zero, for the determined failure zone of θ=90°. FIG. 7 shows two critical production rates, i.e., 0.058 m³/hr and 0.143 m³/hr. The shear failure potential V is less than or equal to zero when the production rate falls in the range of (0.058 m³/hr, 0.143 m³/hr), which includes one or more production rates for the wellbore that is under production and is also stable.

Returning to FIG. 2, at 210, the computer system provides the highest production rate among the one or more determined production rates to control the production rate at the well head of the wellbore under production, in order to increase the production rate of the wellbore while keeping the wellbore stable. In the example described at 208, the production rate of 0.143 m³/hr can be used to increase the production rate of the wellbore while keeping the wellbore stable. In some implementations, the control of the production rate at the well head of a wellbore can be carried out through a wellhead choke. In some cases, during oil or gas production, the production rate can be controlled through the wellhead equipment at the surface. A wellhead can include casing heads, a tubing head, and a Christmas tree. The Christmas tree has valving and choke to control the production rate. The choke usually has ⅛ to ¾ inch in diameter to control the flow rate. The choke can also completely shut off the oil or gas production.

FIG. 8 illustrates an example process 800 for increasing, e.g., maximizing production rate of a wellbore while maintaining wellbore stability. For convenience, process 800 will be described as being performed by a computer system having one or more computers located in one or more locations and programmed appropriately in accordance with this specification. An example of the computer system is the computing system 900 illustrated in FIG. 9 and described below.

At 802, a computer system obtains in-situ stress data, pore pressure data, and formation property data associated with a wellbore.

At 804, the computer system determines, based on the obtained in-situ stress data, pore pressure data, and formation property data, one or more production rates for the wellbore, where the wellbore maintains stability when performing a respective production operation at each of the one or more production rates.

At 806, the computer system provides the determined one or more production rates to control a production rate of the wellbore at a well head of the wellbore, where the production rate of the wellbore at the well head of the wellbore is within a range determined by the one or more production rates.

FIG. 9 is a block diagram of an example computer system 900 that can be used to provide computational functionalities associated with described algorithms, methods, functions, processes, flows, and procedures, according to some implementations of the present disclosure. In some implementations, the computer system performing process 200 or 800 can be the computer system 900, include the computer system 900, or the computer system performing process 200 or 800 can communicate with the computer system 900.

The illustrated computer 902 is intended to encompass any computing device such as a server, a desktop computer, an embedded computer, a laptop/notebook computer, a wireless data port, a smart phone, a personal data assistant (PDA), a tablet computing device, or one or more processors within these devices, including physical instances, virtual instances, or both. The computer 902 can include input devices such as keypads, keyboards, and touch screens that can accept user information. Also, the computer 902 can include output devices that can convey information associated with the operation of the computer 902. The information can include digital data, visual data, audio information, or a combination of information. The information can be presented in a graphical user interface (UI) (or GUI). In some implementations, the inputs and outputs include display ports (such as DVI-I+2× display ports), USB 3.0, GbE ports, isolated DI/O, SATA-III (6.0 Gb/s) ports, mPCle slots, a combination of these, or other ports. In instances of an edge gateway, the computer 902 can include a Smart Embedded Management Agent (SEMA), such as a built-in ADLINK SEMA 2.2, and a video sync technology, such as Quick Sync Video technology supported by ADLINK MSDK+. In some examples, the computer 902 can include the MXE-5400 Series processor-based fanless embedded computer by ADLINK, though the computer 902 can take other forms or include other components.

The computer 902 can serve in a role as a client, a network component, a server, a database, a persistency, or components of a computer system for performing the subject matter described in the present disclosure. The illustrated computer 902 is communicably coupled with a network 930. In some implementations, one or more components of the computer 902 can be configured to operate within different environments, including cloud-computing-based environments, local environments, global environments, and combinations of environments.

At a high level, the computer 902 is an electronic computing device operable to receive, transmit, process, store, and manage data and information associated with the described subject matter. According to some implementations, the computer 902 can also include, or be communicably coupled with, an application server, an email server, a web server, a caching server, a streaming data server, or a combination of servers.

The computer 902 can receive requests over network 930 from a client application (for example, executing on another computer 902). The computer 902 can respond to the received requests by processing the received requests using software applications. Requests can also be sent to the computer 902 from internal users (for example, from a command console), external (or third) parties, automated applications, entities, individuals, systems, and computers.

Each of the components of the computer 902 can communicate using a system bus 903. In some implementations, any or all of the components of the computer 902, including hardware or software components, can interface with each other or the interface 904 (or a combination of both), over the system bus. Interfaces can use an application programming interface (API) 912, a service layer 913, or a combination of the API 912 and service layer 913. The API 912 can include specifications for routines, data structures, and object classes. The API 912 can be either computer-language independent or dependent. The API 912 can refer to a complete interface, a single function, or a set of APIs 912.

The service layer 913 can provide software services to the computer 902 and other components (whether illustrated or not) that are communicably coupled to the computer 902. The functionality of the computer 902 can be accessible for all service consumers using this service layer 913. Software services, such as those provided by the service layer 913, can provide reusable, defined functionalities through a defined interface. For example, the interface can be software written in JAVA, C++, or a language providing data in extensible markup language (XML) format. While illustrated as an integrated component of the computer 902, in alternative implementations, the API 912 or the service layer 913 can be stand-alone components in relation to other components of the computer 902 and other components communicably coupled to the computer 902. Moreover, any or all parts of the API 912 or the service layer 913 can be implemented as child or sub-modules of another software module, enterprise application, or hardware module without departing from the scope of the present disclosure.

The computer 902 can include an interface 904. Although illustrated as a single interface 904 in FIG. 9, two or more interfaces 904 can be used according to particular needs, desires, or particular implementations of the computer 902 and the described functionality. The interface 904 can be used by the computer 902 for communicating with other systems that are connected to the network 930 (whether illustrated or not) in a distributed environment. Generally, the interface 904 can include, or be implemented using, logic encoded in software or hardware (or a combination of software and hardware) operable to communicate with the network 930. More specifically, the interface 904 can include software supporting one or more communication protocols associated with communications. As such, the network 930 or the interface's hardware can be operable to communicate physical signals within and outside of the illustrated computer 902.

The computer 902 includes a processor 905. Although illustrated as a single processor 905 in FIG. 9, two or more processors 905 can be used according to particular needs, desires, or particular implementations of the computer 902 and the described functionality. Generally, the processor 905 can execute instructions and manipulate data to perform the operations of the computer 902, including operations using algorithms, methods, functions, processes, flows, and procedures as described in the present disclosure.

The computer 902 can also include a database 906 that can hold data for the computer 902 and other components connected to the network 930 (whether illustrated or not). For example, database 906 can be an in-memory, conventional, or a database storing data consistent with the present disclosure. In some implementations, the database 906 can be a combination of two or more different database types (for example, hybrid in-memory and conventional databases) according to particular needs, desires, or particular implementations of the computer 902 and the described functionality. Although illustrated as a single database 906 in FIG. 9, two or more databases (of the same, different, or combination of types) can be used according to particular needs, desires, or particular implementations of the computer 902 and the described functionality. While database 906 is illustrated as an internal component of the computer 902, in alternative implementations, database 906 can be external to the computer 902.

The computer 902 also includes a memory 907 that can hold data for the computer 902 or a combination of components connected to the network 930 (whether illustrated or not). Memory 907 can store any data consistent with the present disclosure. In some implementations, memory 907 can be a combination of two or more different types of memory (for example, a combination of semiconductor and magnetic storage) according to particular needs, desires, or particular implementations of the computer 902 and the described functionality. Although illustrated as a single memory 907 in FIG. 9, two or more memories 907 (of the same, different, or combination of types) can be used according to particular needs, desires, or particular implementations of the computer 902 and the described functionality. While memory 907 is illustrated as an internal component of the computer 902, in alternative implementations, memory 907 can be external to the computer 902.

An application 908 can be an algorithmic software engine providing functionality according to particular needs, desires, or particular implementations of the computer 902 and the described functionality. For example, an application 908 can serve as one or more components, modules, or applications 908. Multiple applications 908 can be implemented on the computer 902. Each application 908 can be internal or external to the computer 902.

The computer 902 can also include a power supply 914. The power supply 914 can include a rechargeable or non-rechargeable battery that can be configured to be either user- or non-user-replaceable. In some implementations, the power supply 914 can include power-conversion and management circuits, including recharging, standby, and power management functionalities. In some implementations, the power-supply 914 can include a power plug to allow the computer 902 to be plugged into a wall socket or a power source to, for example, power the computer 902 or recharge a rechargeable battery.

There can be any number of computers 902 associated with, or external to, a computer system including computer 902, with each computer 902 communicating over network 930. Further, the terms “client”, “user”, and other appropriate terminology can be used interchangeably without departing from the scope of the present disclosure. Moreover, the present disclosure contemplates that many users can use one computer 902 and one user can use multiple computers 902.

FIG. 10 illustrates hydrocarbon production operations 1000 that include both one or more field operations 1010 and one or more computational operations 1012, which exchange information and control exploration for the production of hydrocarbons. In some implementations, outputs of techniques of the present disclosure can be performed before, during, or in combination with the hydrocarbon production operations 1000, specifically, for example, cither as field operations 1010 or computational operations 1012, or both.

Examples of field operations 1010 include forming/drilling a wellbore, hydraulic fracturing, producing through the wellbore, injecting fluids (such as water) through the wellbore, to name a few. In some implementations, methods of the present disclosure can trigger or control the field operations 1010. For example, the methods of the present disclosure can generate data from hardware/software including sensors and physical data gathering equipment (e.g., seismic sensors, well logging tools, flow meters, and temperature and pressure sensors). The methods of the present disclosure can include transmitting the data from the hardware/software to the field operations 1010 and responsively triggering the field operations 1010 including, for example, generating plans and signals that provide feedback to and control physical components of the field operations 1010. Alternatively or in addition, the field operations 1010 can trigger the methods of the present disclosure. For example, implementing physical components (including, for example, hardware, such as sensors) deployed in the field operations 1010 can generate plans and signals that can be provided as input or feedback (or both) to the methods of the present disclosure.

Examples of computational operations 1012 include one or more computer systems 1020 that include one or more processors and computer-readable media (e.g., non-transitory computer-readable media) operatively coupled to the one or more processors to execute computer operations to perform the methods of the present disclosure. The computational operations 1012 can be implemented using one or more databases 1018, which store data received from the field operations 1010 and/or generated internally within the computational operations 1012 (e.g., by implementing the methods of the present disclosure) or both. For example, the one or more computer systems 1020 process inputs from the field operations 1010 to assess conditions in the physical world, the outputs of which are stored in the databases 1018. For example, seismic sensors of the field operations 1010 can be used to perform a seismic survey to map subterranean features, such as facies and faults. In performing a seismic survey, seismic sources (e.g., seismic vibrators or explosions) generate seismic waves that propagate in the earth and seismic receivers (e.g., geophones) measure reflections generated as the seismic waves interact with boundaries between layers of a subsurface formation. The source and received signals are provided to the computational operations 1012 where they are stored in the databases 1018 and analyzed by the one or more computer systems 1020.

In some implementations, one or more outputs 1022 generated by the one or more computer systems 1020 can be provided as feedback/input to the field operations 1010 (either as direct input or stored in the databases 1018). The field operations 1010 can use the feedback/input to control physical components used to perform the field operations 1010 in the real world.

For example, the computational operations 1012 can process the seismic data to generate three-dimensional (3D) maps of the subsurface formation. The computational operations 1012 can use these 3D maps to provide plans for locating and drilling exploratory wells. In some operations, the exploratory wells are drilled using logging-while-drilling (LWD) techniques which incorporate logging tools into the drill string. LWD techniques can enable the computational operations 1012 to process new information about the formation and control the drilling to adjust to the observed conditions in real-time.

The one or more computer systems 1020 can update the 3D maps of the subsurface formation as information from one exploration well is received and the computational operations 1012 can adjust the location of the next exploration well based on the updated 3D maps. Similarly, the data received from production operations can be used by the computational operations 1012 to control components of the production operations. For example, production well and pipeline data can be analyzed to predict slugging in pipelines leading to a refinery and the computational operations 1012 can control machine operated valves upstream of the refinery to reduce the likelihood of plant disruptions that run the risk of taking the plant offline.

In some implementations of the computational operations 1012, customized user interfaces can present intermediate or final results of the above-described processes to a user. Information can be presented in one or more textual, tabular, or graphical formats, such as through a dashboard. The information can be presented at one or more on-site locations (such as at an oil well or other facility), on the Internet (such as on a webpage), on a mobile application (or app), or at a central processing facility.

The presented information can include feedback, such as changes in parameters or processing inputs, that the user can select to improve a production environment, such as in the exploration, production, and/or testing of petrochemical processes or facilities. For example, the feedback can include parameters that, when selected by the user, can cause a change to, or an improvement in, drilling parameters (including drill bit speed and direction) or overall production of a gas or oil well. The feedback, when implemented by the user, can improve the speed and accuracy of calculations, streamline processes, improve models, and solve problems related to efficiency, performance, safety, reliability, costs, downtime, and the need for human interaction.

In some implementations, the feedback can be implemented in real-time, such as to provide an immediate or near-immediate change in operations or in a model. The term real-time (or similar terms as understood by one of ordinary skill in the art) means that an action and a response are temporally proximate such that an individual perceives the action and the response occurring substantially simultaneously. For example, the time difference for a response to display (or for an initiation of a display) of data following the individual's action to access the data can be less than 1 millisecond (ms), less than 1 second(s), or less than 5 s. While the requested data need not be displayed (or initiated for display) instantaneously, it is displayed (or initiated for display) without any intentional delay, taking into account processing limitations of a described computing system and time required to, for example, gather, accurately measure, analyze, process, store, or transmit the data.

Events can include readings or measurements captured by downhole equipment such as sensors, pumps, bottom hole assemblies, or other equipment. The readings or measurements can be analyzed at the surface, such as by using applications that can include modeling applications and machine learning. The analysis can be used to generate changes to settings of downhole equipment, such as drilling equipment. In some implementations, values of parameters or other variables that are determined can be used automatically (such as through using rules) to implement changes in oil or gas well exploration, production/drilling, or testing. For example, outputs of the present disclosure can be used as inputs to other equipment and/or systems at a facility. This can be especially useful for systems or various pieces of equipment that are located several meters or several miles apart, or are located in different countries or other jurisdictions.

Implementations of the subject matter and the functional operations described in this specification can be implemented in digital electronic circuitry, in tangibly embodied computer software or firmware; in computer hardware, including the structures disclosed in this specification and their structural equivalents; or in combinations of one or more of them. Software implementations of the described subject matter can be implemented as one or more computer programs. Each computer program can include one or more modules of computer program instructions encoded on a tangible, non-transitory, computer-readable computer-storage medium for execution by, or to control the operation of, data processing apparatus. Alternatively, or additionally, the program instructions can be encoded in/on an artificially generated propagated signal. For example, the signal can be a machine-generated electrical, optical, or electromagnetic signal that is generated to encode information for transmission to a suitable receiver apparatus for execution by a data processing apparatus. The computer-storage medium can be a machine-readable storage device, a machine-readable storage substrate, a random or serial access memory device, or a combination of computer-storage mediums.

The terms “data processing apparatus”, “computer”, and “electronic computer device” (or equivalent as understood by one of ordinary skill in the art) refer to data processing hardware. For example, a data processing apparatus can encompass all kinds of apparatuses, devices, and machines for processing data, including by way of example, a programmable processor, a computer, or multiple processors or computers. The apparatus can also include special purpose logic circuitry including, for example, a central processing unit (CPU), a field programmable gate array (FPGA), or an application specific integrated circuit (ASIC). In some implementations, the data processing apparatus or special purpose logic circuitry (or a combination of the data processing apparatus and special purpose logic circuitry) can be hardware- or software-based (or a combination of both hardware- and software-based). The apparatus can optionally include code that creates an execution environment for computer programs, for example, code that constitutes processor firmware, a protocol stack, a database management system, an operating system, or a combination of execution environments. The present disclosure contemplates the use of data processing apparatuses with or without conventional operating systems, for example, Linux, Unix, Windows, Mac OS, Android, or iOS.

A computer program, which can also be referred to or described as a program, software, a software application, a module, a software module, a script, or code can be written in any form of programming language. Programming languages can include, for example, compiled languages, interpreted languages, declarative languages, or procedural languages. Programs can be deployed in any form, including as stand-alone programs, modules, components, subroutines, or units for use in a computing environment. A computer program can, but need not, correspond to a file in a file system. A program can be stored in a portion of a file that holds other programs or data, for example, one or more scripts stored in a markup language document; in a single file dedicated to the program in question; or in multiple coordinated files storing one or more modules, sub programs, or portions of code. A computer program can be deployed for execution on one computer or on multiple computers that are located, for example, at one site or distributed across multiple sites that are interconnected by a communication network. While portions of the programs illustrated in the various figures may be shown as individual modules that implement the various features and functionality through various objects, methods, or processes; the programs can instead include a number of sub-modules, third-party services, components, and libraries. Conversely, the features and functionality of various components can be combined into single components as appropriate. Thresholds used to make computational determinations can be statically, dynamically, or both statically and dynamically determined.

The methods, processes, or logic flows described in this specification can be performed by one or more programmable computers executing one or more computer programs to perform functions by operating on input data and generating output. The methods, processes, or logic flows can also be performed by, and apparatus can also be implemented as, special purpose logic circuitry, for example, a CPU, an FPGA, or an ASIC.

Computers suitable for the execution of a computer program can be based on one or more of general and special purpose microprocessors and other kinds of CPUs. The elements of a computer are a CPU for performing or executing instructions and one or more memory devices for storing instructions and data. Generally, a CPU can receive instructions and data from (and write data to) a memory. A computer can also include, or be operatively coupled to, one or more mass storage devices for storing data. In some implementations, a computer can receive data from, and transfer data to, the mass storage devices including, for example, magnetic, magneto optical disks, or optical disks. Moreover, a computer can be embedded in another device, for example, a mobile telephone, a personal digital assistant (PDA), a mobile audio or video player, a game console, a global positioning system (GPS) receiver, or a portable storage device such as a universal serial bus (USB) flash drive.

Computer readable media (transitory or non-transitory, as appropriate) suitable for storing computer program instructions and data can include all forms of permanent/non-permanent and volatile/non-volatile memory, media, and memory devices. Computer readable media can include, for example, semiconductor memory devices such as random access memory (RAM), read only memory (ROM), phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), and flash memory devices. Computer readable media can also include, for example, magnetic devices such as tape, cartridges, cassettes, and internal/removable disks. Computer readable media can also include magneto optical disks, optical memory devices, and technologies including, for example, digital video disc (DVD), CD ROM, DVD+/−R, DVD-RAM, DVD-ROM, HD-DVD, and BLURAY. The memory can store various objects or data, including caches, classes, frameworks, applications, modules, backup data, jobs, web pages, web page templates, data structures, database tables, repositories, and dynamic information. Types of objects and data stored in memory can include parameters, variables, algorithms, instructions, rules, constraints, and references. Additionally, the memory can include logs, policies, security or access data, and reporting files. The processor and the memory can be supplemented by, or incorporated in, special purpose logic circuitry.

Implementations of the subject matter described in the present disclosure can be implemented on a computer having a display device for providing interaction with a user, including displaying information to (and receiving input from) the user. Types of display devices can include, for example, a cathode ray tube (CRT), a liquid crystal display (LCD), a light-emitting diode (LED), or a plasma monitor. Display devices can include a keyboard and pointing devices including, for example, a mouse, a trackball, or a trackpad. User input can also be provided to the computer through the use of a touchscreen, such as a tablet computer surface with pressure sensitivity or a multi-touch screen using capacitive or electric sensing. Other kinds of devices can be used to provide for interaction with a user, including to receive user feedback, for example, sensory feedback including visual feedback, auditory feedback, or tactile feedback. Input from the user can be received in the form of acoustic, speech, or tactile input. In addition, a computer can interact with a user by sending documents to, and receiving documents from, a device that is used by the user. For example, the computer can send web pages to a web browser on a user's client device in response to requests received from the web browser.

The term “graphical user interface,” or “GUI,” can be used in the singular or the plural to describe one or more graphical user interfaces and each of the displays of a particular graphical user interface. Therefore, a GUI can represent any graphical user interface, including, but not limited to, a web browser, a touch screen, or a command line interface (CLI) that processes information and efficiently presents the information results to the user. In general, a GUI can include a plurality of user interface (UI) elements, some or all associated with a web browser, such as interactive fields, pull-down lists, and buttons. These and other UI elements can be related to or represent the functions of the web browser. Implementations of the subject matter described in this specification can be implemented in a computing system that includes a back end component, for example, as a data server, or that includes a middleware component, for example, an application server. Moreover, the computing system can include a front-end component, for example, a client computer having one or both of a graphical user interface or a Web browser through which a user can interact with the computer. The components of the system can be interconnected by any form or medium of wireline or wireless digital data communication (or a combination of data communication) in a communication network. Examples of communication networks include a local area network (LAN), a radio access network (RAN), a metropolitan area network (MAN), a wide area network (WAN), Worldwide Interoperability for Microwave Access (WIMAX), a wireless local area network (WLAN) (for example, using 802.11 a/b/g/n or 802.20 or a combination of protocols), all or a portion of the Internet, or any other communication system or systems at one or more locations (or a combination of communication networks). The network can communicate with, for example, Internet Protocol (IP) packets, frame relay frames, asynchronous transfer mode (ATM) cells, voice, video, data, or a combination of communication types between network addresses.

The computing system can include clients and servers. A client and server can generally be remote from each other and can typically interact through a communication network. The relationship of client and server can arise by virtue of computer programs running on the respective computers and having a client-server relationship.

Cluster file systems can be any file system type accessible from multiple servers for read and update. Locking or consistency tracking may not be necessary since the locking of exchange file system can be done at application layer. Furthermore, Unicode data files can be different from non-Unicode data files.

While this specification contains many specific implementation details, these should not be construed as limitations on the scope of what may be claimed, but rather as descriptions of features that may be specific to particular implementations. Certain features that are described in this specification in the context of separate implementations can also be implemented, in combination, or in a single implementation. Conversely, various features that are described in the context of a single implementation can also be implemented in multiple implementations, separately, or in any suitable sub-combination. Moreover, although previously described features may be described as acting in certain combinations and even initially claimed as such, one or more features from a claimed combination can, in some cases, be excised from the combination, and the claimed combination may be directed to a sub-combination or variation of a sub-combination.

Particular implementations of the subject matter have been described. Other implementations, alterations, and permutations of the described implementations are within the scope of the following claims as will be apparent to those skilled in the art. While operations are depicted in the drawings or claims in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order, or that all illustrated operations be performed (some operations may be considered optional), to achieve desirable results. In certain circumstances, multitasking or parallel processing (or a combination of multitasking and parallel processing) may be advantageous and performed as deemed appropriate.

Moreover, the separation or integration of various system modules and components in the previously described implementations should not be understood as requiring such separation or integration in all implementations; and it should be understood that the described program components and systems can generally be integrated together in a single software product or packaged into multiple software products.

Accordingly, the previously described example implementations do not define or constrain the present disclosure. Other changes, substitutions, and alterations are also possible without departing from the spirit and scope of the present disclosure.

Furthermore, any claimed implementation is considered to be applicable to at least a computer-implemented method; a non-transitory, computer-readable medium storing computer-readable instructions to perform the computer-implemented method; and a computer system comprising a computer memory interoperably coupled with a hardware processor configured to perform the computer-implemented method or the instructions stored on the non-transitory, computer-readable medium.

EMBODIMENTS

Embodiment 1: A computer-implemented method comprising obtaining in-situ stress data, pore pressure data, and formation property data associated with a wellbore; determining, based on the obtained in-situ stress data, pore pressure data, and formation property data, one or more production rates for the wellbore, wherein the wellbore maintains stability when performing a respective production operation at each of the one or more production rates; and providing the determined one or more production rates to control a production rate of the wellbore at a well head of the wellbore, wherein the production rate of the wellbore at the well head of the wellbore is within a range determined by the one or more production rates.

Embodiment 2: The computer-implemented method of embodiment 1, wherein the formation property data comprises at least one of Young's modulus, Poisson's ratio, rock strength, Biot's coefficient, Skempton's coefficient, or permeability associated with the wellbore.

Embodiment 3: The computer-implemented method of embodiment 1 or 2, wherein obtaining the in-situ stress data, the pore pressure data, and the formation property data comprises obtaining the in-situ stress data, the pore pressure data, and the formation property data from offset wells data, well tests, laboratory measurements, or well log analysis associated with the wellbore.

Embodiment 4: The computer-implemented method of any one of embodiments 1 to 3, wherein determining the one or more production rates comprises determining, at the production rate of the wellbore, a shear failure potential around the wellbore based on a shear failure criterion.

Embodiment 5: The computer-implemented method of embodiment 4, wherein the shear failure criterion comprises a Mohr Coulomb criterion.

Embodiment 6: The computer-implemented method of embodiment 4 or 5, wherein determining the one or more production rates comprises: determining, at the production rate of the wellbore, a failure zone having the highest shear failure potential among a plurality of zones around the wellbore; and determining the one or more production rates for the determined failure zone.

Embodiment 7: The computer-implemented method of any one of embodiments 1 to 6, wherein determining the one or more production rates for the determined failure zone comprises determining the one or more production rates for the determined failure zone based on constitutive equations for a poroelastic porous medium.

Embodiment 8: The computer-implemented method of any one of embodiments 1 to 7, wherein providing the determined one or more production rates to control the production rate of the wellbore comprises: determine the largest production rate among the determined one or more production rates; and providing the largest production rate to control the production rate of the wellbore.

Embodiment 9: A non-transitory computer-readable medium storing one or more instructions executable by a computer system to perform operations comprising: obtaining in-situ stress data, pore pressure data, and formation property data associated with a wellbore; determining, based on the obtained in-situ stress data, pore pressure data, and formation property data, one or more production rates for the wellbore, wherein the wellbore maintains stability when performing a respective production operation at each of the one or more production rates; and providing the determined one or more production rates to control a production rate of the wellbore at a well head of the wellbore, wherein the production rate of the wellbore at the well head of the wellbore is within a range determined by the one or more production rates.

Embodiment 10: The non-transitory computer-readable medium of embodiment 9, wherein the formation property data comprises at least one of Young's modulus, Poisson's ratio, rock strength, Biot's coefficient, Skempton's coefficient, or permeability associated with the wellbore.

Embodiment 11: The non-transitory computer-readable medium of embodiment 9 or 10, wherein obtaining the in-situ stress data, the pore pressure data, and the formation property data comprises obtaining the in-situ stress data, the pore pressure data, and the formation property data from offset wells data, well tests, laboratory measurements, or well log analysis associated with the wellbore.

Embodiment 12: The non-transitory computer-readable medium of any one of embodiments 9 to 11, wherein determining the one or more production rates comprises determining, at the production rate of the wellbore, a shear failure potential around the wellbore based on a shear failure criterion.

Embodiment 13: The non-transitory computer-readable medium of embodiment 12, wherein determining the one or more production rates comprises: determining, at the production rate of the wellbore, a failure zone having the highest shear failure potential among a plurality of zones around the wellbore; and determining the one or more production rates for the determined failure zone.

Embodiment 14: The non-transitory computer-readable medium of any one of embodiments 9 to 13, wherein determining the one or more production rates for the determined failure zone comprises determining the one or more production rates for the determined failure zone based on constitutive equations for a poroclastic porous medium.

Embodiment 15: A computer-implemented system, comprising one or more computers; and one or more computer memory devices interoperably coupled with the one or more computers and having tangible, non-transitory, machine-readable media storing one or more instructions that, when executed by the one or more computers, perform one or more operations comprising: obtaining in-situ stress data, pore pressure data, and formation property data associated with a wellbore; determining, based on the obtained in-situ stress data, pore pressure data, and formation property data, one or more production rates for the wellbore, wherein the wellbore maintains stability when performing a respective production operation at each of the one or more production rates; and providing the determined one or more production rates to control a production rate of the wellbore at a well head of the wellbore, wherein the production rate of the wellbore at the well head of the wellbore is within a range determined by the one or more production rates.

Embodiment 16: The computer-implemented system of embodiment 15, wherein the formation property data comprises at least one of Young's modulus, Poisson's ratio, rock strength, Biot's coefficient, Skempton's coefficient, or permeability associated with the wellbore.

Embodiment 17: The computer-implemented system of embodiment 15 or 16, wherein obtaining the in-situ stress data, the pore pressure data, and the formation property data comprises obtaining the in-situ stress data, the pore pressure data, and the formation property data from offset wells data, well tests, laboratory measurements, or well log analysis associated with the wellbore.

Embodiment 18: The computer-implemented system of any one of embodiments 15 to 17, wherein determining the one or more production rates comprises determining, at the production rate of the wellbore, a shear failure potential around the wellbore based on a shear failure criterion.

Embodiment 19: The computer-implemented system of embodiment 18, wherein determining the one or more production rates comprises: determining, at the production rate of the wellbore, a failure zone having the highest shear failure potential among a plurality of zones around the wellbore; and determining the one or more production rates for the determined failure zone.

Embodiment 20: The computer-implemented system of any one of embodiments 15 to 19, wherein determining the one or more production rates for the determined failure zone comprises determining the one or more production rates for the determined failure zone based on constitutive equations for a poroelastic porous medium.

Claims

1. A computer-implemented method comprising: obtaining in-situ stress data, pore pressure data, and formation property data associated with a wellbore;determining, based on the obtained in-situ stress data, pore pressure data, and formation property data, one or more production rates for the wellbore, wherein the wellbore maintains stability when performing a respective production operation at each of the one or more production rates; andproviding the determined one or more production rates to control a production rate of the wellbore at a well head of the wellbore, wherein the production rate of the wellbore at the well head of the wellbore is within a range determined by the one or more production rates.

2. The computer-implemented method of claim 1, wherein the formation property data comprises at least one of Young's modulus, Poisson's ratio, rock strength, Biot's coefficient, Skempton's coefficient, or permeability associated with the wellbore.

3. The computer-implemented method of claim 1, wherein obtaining the in-situ stress data, the pore pressure data, and the formation property data comprises obtaining the in-situ stress data, the pore pressure data, and the formation property data from offset wells data, well tests, laboratory measurements, or well log analysis associated with the wellbore.

4. The computer-implemented method of claim 1, wherein determining the one or more production rates comprises determining, at the production rate of the wellbore, a shear failure potential around the wellbore based on a shear failure criterion.

5. The computer-implemented method of claim 4, wherein the shear failure criterion comprises a Mohr Coulomb criterion.

6. The computer-implemented method of claim 4, wherein determining the one or more production rates comprises: determining, at the production rate of the wellbore, a failure zone having the highest shear failure potential among a plurality of zones around the wellbore; anddetermining the one or more production rates for the determined failure zone.

7. The computer-implemented method of claim 1, wherein determining the one or more production rates for the determined failure zone comprises determining the one or more production rates for the determined failure zone based on constitutive equations for a poroelastic porous medium.

8. The computer-implemented method of claim 1, wherein providing the determined one or more production rates to control the production rate of the wellbore comprises: determine the largest production rate among the determined one or more production rates; andproviding the largest production rate to control the production rate of the wellbore.

9. A non-transitory computer-readable medium storing one or more instructions executable by a computer system to perform operations comprising: obtaining in-situ stress data, pore pressure data, and formation property data associated with a wellbore;determining, based on the obtained in-situ stress data, pore pressure data, and formation property data, one or more production rates for the wellbore, wherein the wellbore maintains stability when performing a respective production operation at each of the one or more production rates; andproviding the determined one or more production rates to control a production rate of the wellbore at a well head of the wellbore, wherein the production rate of the wellbore at the well head of the wellbore is within a range determined by the one or more production rates.

10. The non-transitory computer-readable medium of claim 9, wherein the formation property data comprises at least one of Young's modulus, Poisson's ratio, rock strength, Biot's coefficient, Skempton's coefficient, or permeability associated with the wellbore.

11. The non-transitory computer-readable medium of claim 9, wherein obtaining the in-situ stress data, the pore pressure data, and the formation property data comprises obtaining the in-situ stress data, the pore pressure data, and the formation property data from offset wells data, well tests, laboratory measurements, or well log analysis associated with the wellbore.

12. The non-transitory computer-readable medium of claim 9, wherein determining the one or more production rates comprises determining, at the production rate of the wellbore, a shear failure potential around the wellbore based on a shear failure criterion.

13. The non-transitory computer-readable medium of claim 12, wherein determining the one or more production rates comprises: determining, at the production rate of the wellbore, a failure zone having the highest shear failure potential among a plurality of zones around the wellbore; anddetermining the one or more production rates for the determined failure zone.

14. The non-transitory computer-readable medium of claim 9, wherein determining the one or more production rates for the determined failure zone comprises determining the one or more production rates for the determined failure zone based on constitutive equations for a poroelastic porous medium.

15. A computer-implemented system, comprising: one or more computers; andone or more computer memory devices interoperably coupled with the one or more computers and having tangible, non-transitory, machine-readable media storing one or more instructions that, when executed by the one or more computers, cause the computer-implemented system to perform one or more operations comprising: obtaining in-situ stress data, pore pressure data, and formation property data associated with a wellbore;determining, based on the obtained in-situ stress data, pore pressure data, and formation property data, one or more production rates for the wellbore, wherein the wellbore maintains stability when performing a respective production operation at each of the one or more production rates; andproviding the determined one or more production rates to control a production rate of the wellbore at a well head of the wellbore, wherein the production rate of the wellbore at the well head of the wellbore is within a range determined by the one or more production rates.

16. The computer-implemented system of claim 15, wherein the formation property data comprises at least one of Young's modulus, Poisson's ratio, rock strength, Biot's coefficient, Skempton's coefficient, or permeability associated with the wellbore.

17. The computer-implemented system of claim 15, wherein obtaining the in-situ stress data, the pore pressure data, and the formation property data comprises obtaining the in-situ stress data, the pore pressure data, and the formation property data from offset wells data, well tests, laboratory measurements, or well log analysis associated with the wellbore.

18. The computer-implemented system of claim 15, wherein determining the one or more production rates comprises determining, at the production rate of the wellbore, a shear failure potential around the wellbore based on a shear failure criterion.

19. The computer-implemented system of claim 18, wherein determining the one or more production rates comprises: determining, at the production rate of the wellbore, a failure zone having the highest shear failure potential among a plurality of zones around the wellbore; anddetermining the one or more production rates for the determined failure zone.

20. The computer-implemented system of claim 15, wherein determining the one or more production rates for the determined failure zone comprises determining the one or more production rates for the determined failure zone based on constitutive equations for a poroclastic porous medium.