The present invention relates to a method for characterizing external surroundings of a casing string. More specifically, the method comprises transmitting acoustic signals from a source located inside a multiple casing string for characterizing abnormalities outside a multiple casing string.
The present invention enables estimation of parameters of a propagating wave field, such as the direction of propagation in 3D space of an acoustic wave from borehole-acoustic data. The estimation technique uses the phase delays between recordings made by the individual receivers related to a plane wave travelling across the receiver array. The estimated plane waves would include the wave field generated directly by the acoustic source, as well as refracted and reflected components of these fields. The technique can be used with overlapping wave fields. This could potentially lead to significant improvements in the quality of formation properties that is estimated from full-waveform data, obtained either from wireline or from while-drilling sonic data.
We also show, using ultrasonic data, that we can use these propagating modes to measure the location and the reflectivity abnormalities outside of multiple casing strings, allowing inference about material properties behind multiple casing strings.
Since the original work by Hornby (1989), with a 12-receiver station tool (EVA, developed by Elf/CGG), Sonic Imaging has been attempted with varying success using a number of different implementations. The root cause for most of the problems with any of these variations is that the well bore is an excellent guide for acoustic waves. This acoustic wave guide would cause energy reflected by the well surroundings to be over-powered by energy trapped in the well bore.
In 2002 and early 2003, a new set of processing algorithms were developed (Haldorsen et al., 2005) using adaptive filters to control the Stoneley waves. These algorithms allowed the use of much shorter source-receiver offsets. A short source-receiver offset is geometrically much more favorable for near-wellbore reflection imaging.
The reflection data are converted into images of the formation using synthetic-aperture processing.
Adaptive filters were also used with the receivers mounted around the perimeter of the tool to determine the azimuth of the acoustic reflectors, in effect creating a 3D image around the borehole. With the new algorithms, Sonic Imaging (with the acronym BARS from Borehole Acoustic Reflection Survey) could be applied to data acquired with the Sonic Scanner in its standard configuration, allowing data produced by any sonic job to be used for imaging.
Ultrasonic pulse-echo techniques were initially developed as a form of acoustic caliper technique (Havira, 1986). Hayman et al. (1994) realizing that the high frequencies, 290-550 kHz, allowed the imaging of the backside of the casing, allowing ultrasonic tools to be used for estimating the thickness of the casing wall. However, the extremely high contrast between the steel of the casing and the fluid or cement behind the casing, would set up standing waves that made it very difficult to make sense of components of the signal that actually had penetrated into the annulus behind the casing.
Zeroug and Froelich (2003) realized that a flexural mode in the casing, traveling along the well, would leak into the annulus, be reflected from features in the annulus, and by recording such waves, that could be able to image the structures behind the casing.
This is the technology behind the Schlumberger Isolation Scanner tool, designed to specifically measure waves refracted along the well, with the purpose to improve the characterization of the annular environment (van Kuijk et al, 2005). The Isolation Scanner has both a pulse-echo transceiver and a combination of transmitter and receivers designed to excite and record flexural waves in the casing. The tool, which rotates at the bottom of the tool, scans the casing at predetermined intervals allowing 360° azimuthal coverage to help identifying channels in the cement and confirming the effectiveness of a cement job for zonal isolation.
The acoustic waves emitted from an acoustic tool in a cased well scattered, reflected and refracted from inhomogeneities in the formation outside the inner casing (see
According to the present invention acoustic data, generated by a known source and recorded by an array of acoustic receivers mounted on the surface of a cylindrical tool in a wellbore, is separated into propagating plane waves and the propagation parameters for these plane-wave components is estimated individually. This method allows separation of borehole modes from body waves, and where the body waves are used for imaging formation features outside of the well bore. Similarly, the ray parameters of the plane-wave components give information about the direction to a feature in the formation that acts as an acoustic scatter (for body waves), and for the tool eccentricity (for borehole modes).
By using ultrasonic data, these propagating modes is used for measuring the location and the reflectivity of abnormalities outside of multiple casing strings, allowing inference about material properties behind multiple casing strings.
A method for characterizing properties outside a multiple casing string, comprising transmitting acoustic signals from a source located inside said multiple casing string; recording received signals on an array of acoustic receivers mounted on a longitudinal cylindrical tool inside said multiple casing string, and processing received signals by performing the following steps:
Other features of the invention are defined in the claims.
The patent or application file contains at least one drawing executed in color. Copies of this patent or patent application publication with color drawing(s) will be provided by the Office upon request and payment of the necessary fee.
The invention will now be described in detail with reference to the drawings where:
Several potentially severe problems were solved by using the Sonic Scanner in its standard configuration.
The large dynamic range of Sonic Scanner (giving digitized data at 16-bit resolution) allows weak reflections to be recorded in the presence of powerful modes trapped in the well bore.
The simply shaped construction of Sonic Scanner makes it possible to apply powerful model-guided adaptive filters to separate the strong, guided modes from the weak reflections.
13 receivers at separate eight azimuths makes it possible to determine at which side of the well bore a reflector is located.
The Schlumberger Isolation Scanner© tool is specifically designed to measure waves refracted along the well. The tool has both a pulse-echo transceiver and a system consisting of a combination of a single transmitter and two receivers designed to excite and record flexural waves in the casing. The tool, which rotates at the bottom of the tool, scans the casing at predetermined angular intervals allowing 360° azimuthal coverage.
The following example uses field data from the North Sea acquired with said Sonic Scanner© for Statoil. The data are acquired in the deep part of a cased well. The sonic waveforms were acquired within single and double casing.
In
The data in
In the following we will analyze methods for separating highly overlapping components of the well-bore wave field, and explore how the separated wave-field components can be used for imaging the well and its immediate surroundings.
Plane-Wave Decomposition
The near-linear increase in arrival times for the direct arrivals with increasing source-receiver offset in
Aj(x,τjx,ω)=gj(x,ω)eiωτ
where the amplitude factor gj (x,ω) describes the wave-component j, affected by wave-field spreading and absorption, ω denotes the angular frequency, and τjx is the travel time for wave-field component j from the source at 0 to the receiver at location x. This travel time can be written as τjx=sj·x where is the slowness vector (inverse velocity) for the propagating wave. Ignoring the spatial variations in the wave-field function by setting gj (x,ω)=(ω), we can rewrite Equation [1]:
Aj(x,sj,ω)=gj(ω)eiωs
A set of data traces D recorded at receiver rn at a given source-receiver offset xn, can be written as a superposition of the elemental wave-field components:
In order to get simultaneous, unbiased estimates of gj (ω), one could invert Equation [3] by using a method similar to the one described by Hirabayashi et al. (2008). However, for the purpose of testing the concept, we have estimated the set of parameters for one wave-field component at the time, starting with the most coherent. The propagation time for wave-field component k from the source at 0 to the receiver at x is equal to sk·x. By shifting all data traces D by sk·x, the reference time for wave-field component k will refer to the time of the emission from the source (at τ=0), all receivers will have copies of the propagating, elemental wave field gk (ω), aligned to the time of emission at the source. At this reference time, we have:
Summing over the N receivers, we get:
If we require that the propagators for the plane-wave components are approximately orthogonal, in the sense that for j≠k, we have:
With this condition, we get estimates of the wave-field components gk(ω) by time delaying and stacking:
Considering the difference in propagation slowness |s| for the elemental wave forms (mainly compressional, shear and Stoneley), the condition imposed by Equation [6] should be good. However, this condition could also be adversely affected by the spatial and temporal aliasing.
The stacking power for the aligned data as a function of velocity, polar angle θ, and azimuth angle φ is:
Accordingly, the semblance is given by:
The objective would then be, for each elemental wave-field component k, to find the set of parameters s, θ and ω that maximizes the power Pk(s,θ,φ) or the semblance Sk(s,θ,φ). The linear move-outs of the wave-field components seen in the fixed-azimuth data in
The “wave-field stripping process” starts with the wave-field giving the highest semblance value. Having established the parameters for wave-field component 1, we estimate this using either Equation [8] or [9], and remove it. On the residuals, we find the most coherent wave field, etc. By repeating this process 4 times, we find estimates of the 5 most coherent wave-field components (in hierarchical order).
Reflection-Point Mapping
Up to this point, we have made no use of absolute travel times. However, with our estimates of formation velocities, and propagation directions for scattered waves, the travel times will tell the distance to the scatterers.
Let us assume we have a constant-velocity medium at velocity vl and that a wave is generated by a source at point s, scattered at point x and arriving at the receiver at point r at time t. It is well-known from migration theory that x lies on an ellipsoid with the source and receiver at its focal points (see, e.g., Miller et al, 1987). The generator for the ellipsoid is vt, the medium velocity multiplied by the total travel time.
From our measurements, we also know the direction from the receiver towards the scattering point. Pointing back into the formation along the direction the scattered wave arrived, at the azimuth determined above, the scattering point is offset from the mid-point between source and receiver by:
at a distance from the wellbore axis of:
Here, the parameters v and θ are obtained from the plane-wave analysis in the previous section.
Refraction Mapping
The borehole wall is generally associated with a propagating velocity for acoustic waves vs that is larger than the propagation velocity in the fluid vl (which generally is around 1500 m/s). We have a relation between the distance d to the wall of the well and the travel time tn for a direct, refracted wave travelling along the borehole wall from the source to the receiver n offset by a distance Dn, with Dn>>d, from the source:
Here vs and vl are the propagation velocities in the formation and in the fluid-filled wellbore, respectively, assuming that vl<vs, and that both the source and receivers are at the same distance from the wall. This can be solved for the distance to the borehole wall:
This equation gives a mapping directly from travel time to distance away from the tool face. Knowing the distance from the centre of the wellbore to the transmitter and receiver faces, Equation [13] gives a direct measure of the casing radius. We will use this equation to make an image of the borehole wall. However, with a fluid-filled annulus (like in
With a tool with arbitrary centralization in the wellbore, from Equation [13] one can find the difference Δy in the fluid thickness at opposite sides of the tool:
where Δt is the delay between wave-field arrivals at two opposing sides of the tool. Measured by the wave-front tilt θ, the maximum difference in fluid thickness becomes:
where r is the average of the two distances, or typically half the difference between the well diameter and tool diameter. For fixed values of r and Δy, the tilt angle is approximately proportional to the square root of the difference between the formation and the well-fluid velocities.
Wave-Field Decomposition, Application to Field Data, Sonic Scanner
For the data shown in
Having established the parameters for wave-field component 1, we estimate this wave field using Equation 8, and remove it. On the residuals, we find the next most coherent wave field, etc. This process is repeated 4 times, giving estimates of the 5 most coherent components of the wave field (in hierarchical order).
Wave-Field Stripping, Application to Field Data, Sonic Scanner
The “wave-field stripping process” proceeds according to the above, starting with the wave field giving the highest semblance value. Having established the parameters for wave-field component 1, we estimate this using Equation 8, and remove it. On the residuals, we find the most coherent wave field, etc. This process was repeated 4 times, giving estimates of the 5 most coherent components of the wave field (in hierarchical order).
We have applied this decomposition technique to data acquired in the well schematically described in
The data show a rather obvious and significant change in character at a depth (MD) of 3427 m, above which the amplitude for the earliest arrival increases abruptly. It is natural to assume that this is where the cement ends between the 7″ casing and the formation, 34 m above the 3461 m indicated on
This change is further confirmed by the wave-field decomposition analysis, the results of which are summarized in
Refraction Imaging, Application to Field Data, Isolation Scanner
Isolation Scanner acquires data at frequencies between 200 and 500 kHz. The data we show in
The event meandering between the 100 and 180 μs has most likely been refracted along the 9⅝-in casing, indicating that this casing is touching the 7-in casing at several points, at around 2180 m, 220 m and 2310 m, along the 160 m long depth interval.
From
This complete dataset has been migrated, using Equations [12] and [13]. In accordance with Zeroug and Froelich (2003) we assume that the dominant mode, relevant to our objectives, excited in the 7-in pipe is flexural with a propagation velocity of 3240 m/s. For the fluid velocity, we used a value of 1480 m/s. Unfortunately the two receivers available for the Isolation Scanner does not allow us to use the higher-resolution estimation of these velocities, like we could do for the Sonic Scanner data.
A sector of the migrated image is shown in
The spatially connected object described by the picked blue dots in
From the picked events, we next extract their eccentricity relative to the center of the 7-in casing, the average diameter around the azimuths, and the “ovality”-which we define as the difference between the maximum and minimum diameter relative to the average. These parameters are shown in
In
The higher-amplitude event that appears to be cork-screwing around the pipe deeper (red arrows), could be an indication of a channel behind the casing. (We expect the “cork-screwing” to be mostly related to the rotation of the tool as shown in
Although we do not show it in this report, the refraction imaging that we have applied to the Isolation Scanner data, can obviously also be applied to the data acquired with the Sonic Scanner.
This application is based upon and claims the benefit of priority from U.S. Provisional Patent Application 61/950,484, filed on Mar. 10, 2014; the entire contents of which are incorporated herein by reference.
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7149146 | Kuijk | Dec 2006 | B2 |
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20160041287 | Merciu | Feb 2016 | A1 |
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EP 1505252 | Sep 2005 | VG |
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61950484 | Mar 2014 | US |