Method and device for analyzing actual drilling condition of horizontal well and optimizing speed model

Abstract

The invention discloses a method and device for analyzing the actual drilling condition of a horizontal well and optimizing a speed model, and belongs to the technical field of oil-gas exploration. The method comprises the following steps: S1, monitoring the actual drilling well seismic coincidence condition; s2, when mismatching occurs, analyzing a series of strata causing errors, and delimiting a range of a geological anomalous body; s3, sketching an expected output horizon of the target body according to the relationship between the error and the geological anomalous body, and calculating a target body deformation quantity; s4, calculating a speed disturbance quantity according to the range of the geological anomalous body and a target body variable quantity, calculating and smoothing a speed proportion body, and applying disturbance to the speed model; and S5, performing grid chromatography inversion by using the disturbed velocity model depth offset to obtain an optimized velocity model. According to the method, the well-seismic coincidence degree can be effectively improved, and the supporting effect of seismic data on horizontal well drilling is improved; in addition, predictability is achieved, and the situation of well seismic errors caused by the same geological anomalous body cannot be encountered any more during follow-up drilling of the horizontal well and full-well drilling of the adjacent well.

Description

Technical Field

[0001] The invention belongs to the technical field of oil and gas exploration, and relates to a method for analyzing the actual drilling situation of a horizontal well, in particular to a method and a device for analyzing the actual drilling situation of a horizontal well and optimizing a velocity model. Background Art

[0002] In recent years, my country's shale gas exploration and development has entered a critical period of increasing reserves and production. In the process of shale gas development, the horizontal well drilling rate is a key factor that determines the development effect. At present, the horizontal well drilling process mainly relies on geosteering technology for target tracking. Seismic data in the depth domain can reflect the formation trend at a large scale, which plays an important supplementary role in geosteering technology. Not only that, the prediction of the depth of the target by the seismic data in the depth domain can guide the horizontal well to enter the target accurately, and the characterization of the fault can also remind the drillers of risks. Therefore, how to obtain more accurate imaging data in the depth domain is a very important research direction. With the continuous deepening of research, in order to improve the accuracy, the researchers have established the policy of directly using prestack depth migration data to guide horizontal well drilling. The micro-structures and natural fractures in the shale gas development area of ​​the Sichuan Basin are highly developed, and the target layer has a large change in the occurrence, which puts higher requirements on the accuracy of the seismic prestack depth migration data.

[0003] At present, the industry mainly uses grid tomography technology to optimize the velocity model of pre-stack depth migration. Grid tomography technology uses information such as the travel time of reflection waves from CMP gathers to invert the underground velocity change trend in a data-driven manner. However, due to the limitations of seismic data resolution and sampling rate, the velocity model obtained by grid tomography inversion has limited accuracy. In fact, the current depth migration results often do not match the actual drilling.

[0004] In the existing technology, when faced with a situation that does not match the actual drilling, the profile is usually corrected directly based on the existing well seismic errors. This result is usually not predictive, and subsequent drilling is likely to encounter errors of the same origin. Even the correction behavior itself may cause profile distortion, thereby generating new errors and affecting the drilling effect. Summary of the invention

[0005] The purpose of the present invention is to provide a method and device for analyzing the actual drilling situation of a horizontal well and optimizing a velocity model, so as to solve the problem that the actual drilling result of the horizontal well does not match the depth migration result, resulting in poor drilling effect.

[0006] In order to achieve the above object, the technical solution adopted by the present invention is:

[0007] A method for analyzing the actual drilling situation of a horizontal well and optimizing a velocity model comprises the following steps:

[0008] S1. Monitor whether the horizontal well drilling steering model is consistent with the depth domain migration imaging data volume;

[0009] S2. When there is a mismatch, analyze the strata causing the error and define the scope of the geological anomaly;

[0010] S3. Delineate the target body's expected output horizon based on the relationship between the error and the geological anomaly, and calculate the target body's shape variable;

[0011] S4. Calculate the velocity disturbance amount according to the range of the geological anomaly body and the target body shape variable, generate a time domain velocity proportional body, smooth the velocity proportional body, and apply disturbance to the velocity model;

[0012] S5. Use the disturbed velocity model to perform depth migration processing and perform grid tomography inversion to obtain the optimized velocity model.

[0013] As a limitation, step S2 specifically includes:

[0014] When a mismatch occurs, the strata causing the error are analyzed by combining plane and section, and the lateral range of the stratigraphic top and stratigraphic bottom of the geological anomaly is delineated in the time domain migration imaging data volume and the depth domain migration imaging data volume.

[0015] As another limitation, step S3 specifically includes:

[0016] According to the relationship between the error and the thickness of the geological anomaly, the depth change of the target body caused by the geological anomaly is calculated, and the expected output layer H of the target body in the depth domain is outlined. * , and calculate the target shape variable △H:

[0017] △H=H * -H

[0018] Where △H is the target shape variable; H * is the expected output layer of the target in the depth domain; H is the layer of the target in the depth domain migration imaging data volume.

[0019] As a third limitation, the step S4 specifically includes:

[0020] S41. Calculate the velocity disturbance according to the range of the geological anomaly and the target shape. The calculation formula is:

[0021] U=(D b -D t +△H) / (D b -D t )

[0022] Where U is the velocity disturbance; D b D is the stratum bottom of the geological anomaly in the depth domain migration imaging data volume; tis the top of the stratum of the geological anomaly in the depth domain migration imaging data volume; △H is the target body shape variable;

[0023] S42. Generate time domain velocity ratio volume: In the time domain migration imaging data volume, the top of the geological anomaly body T t and the bottom of the formation T b Fill U between the two and fill 1 in the remaining space to generate a time domain velocity proportional volume S T ;

[0024] S43. Smoothed time domain velocity ratio S T Get SS T , and the time domain velocity model V T Apply a perturbation:

[0025] UV T =SS T *V T

[0026] Where, UV T is the time domain velocity model after disturbance; SS T V is the velocity ratio in the time domain after smoothing; T is the time domain velocity model;

[0027] S44. The time domain velocity model UV after disturbance T Convert to the depth domain and obtain the perturbed depth domain velocity model UV D .

[0028] As a fourth limitation, the step S5 specifically includes:

[0029] The disturbed depth domain velocity model is used for migration and multiple rounds of grid tomography inversion are performed until the velocity is stable and the gathers are flattened, thus obtaining the optimized velocity model.

[0030] As a fifth limitation, the step S5 further includes:

[0031] S6. Use the optimized velocity model to perform overall depth migration, obtain a new depth domain migration imaging data volume, and monitor whether it is consistent with the horizontal well drilling guidance model.

[0032] The present invention also provides a device for analyzing the actual drilling situation of a horizontal well and optimizing a velocity model, comprising:

[0033] A judgment module is used to monitor whether the horizontal well drilling guidance model and the depth domain migration imaging data volume are consistent;

[0034] The geological anomaly analysis module is used to analyze the strata causing the error and define the scope of the geological anomaly when there is a mismatch;

[0035] The target body shape variable calculation module is used to outline the target body's expected output layer according to the relationship between the error and the geological anomaly body, and calculate the target body shape variable;

[0036] The velocity perturbation module is used to calculate the velocity perturbation amount according to the range of the geological anomaly body and the target body shape variable, generate the time domain velocity proportional body, smooth the velocity proportional body, and apply perturbation to the velocity model;

[0037] The velocity model optimization module uses the disturbed velocity model to perform depth migration processing and grid tomography inversion to obtain an optimized velocity model.

[0038] Due to the adoption of the above technical solution, the present invention has the following technical advances compared with the prior art:

[0039] The present invention provides a method and device for analyzing the actual drilling situation of a horizontal well and optimizing a velocity model. The method determines the stratum that generates errors through analysis, delimits the scope of geological anomalies, estimates the influence of geological anomalies, calculates velocity ratio bodies, applies disturbances to the velocity model, and then uses grid tomography to update and stabilize the velocity model, thereby finally eliminating the errors generated by such geological anomalies, thereby effectively improving the consistency between well and seismic data and enhancing the supporting effect of seismic data on horizontal well drilling. In addition, the method is predictive, and the subsequent drilling of the horizontal well and the full well drilling of the adjacent well will no longer encounter the situation where the same geological anomalies cause well and seismic errors. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 is a flowchart of the method in Example 1;

[0041] Figure 2 It is a cross-sectional view along the well trajectory of horizontal well A in Example 1;

[0042] Figure 3 is the depth domain velocity model in Example 1;

[0043] Figure 4 The optimized depth domain velocity model in Example 1;

[0044] Figure 5 This is a cross-sectional view of the horizontal well A along the well trajectory after the velocity model is optimized in Example 1;

[0045] Figure 6 Schematic diagram of the well trajectory and position of horizontal well A and horizontal well B in Example 1;

[0046] Figure 7 This is a cross-sectional view of horizontal well B along the well trajectory after the velocity model is optimized in Example 1. DETAILED DESCRIPTION

[0047] The present invention is further described in detail below by specific examples. It should be understood that the described examples are only used to explain the present invention, and are not intended to limit the present invention.

[0048] Example 1 A method for analyzing the actual drilling situation of a horizontal well and optimizing the velocity model

[0049] This embodiment discloses a method for analyzing the actual drilling situation of a horizontal well and optimizing a velocity model. The flow chart is as follows: Figure 1 As shown, this embodiment applies the method in a shale gas horizontal well operation in a certain area of ​​Luzhou, and specifically includes the following steps:

[0050] S1. Monitoring the seismic matching of actual drilling

[0051] Monitor whether the drilling guidance model of horizontal well A is consistent with the depth domain migration imaging data volume. The results are as follows: Figure 2 As shown by Figure 2 It can be seen that the wellbore and seismic data did not match during the drilling of horizontal well A. The actual drilling results of horizontal well A confirmed that the micro-structure in the profile of the depth domain migration imaging data volume should not exist.

[0052] S2. When there is a mismatch, analyze the strata that caused the error and define the scope of the geological anomaly

[0053] Time-to-depth conversion, using the depth domain velocity model V D (like Figure 3 As shown in the figure), the depth domain is offset to the imaging data volume P D The depth domain velocity model itself is converted to the time domain to obtain the time domain migration imaging data volume P T and the time domain velocity model V T .

[0054] From the target body upward, the horizontal slices and along-layer slices (planar analysis) of the seismic data are analyzed layer by layer from depth to shallowness, and the inline, crossline sections and sections parallel and perpendicular to the A well trajectory (profile analysis) are gradually analyzed around the mismatching position to determine the strata and geological anomalies that cause the error.

[0055] Through the combined analysis of plane and section, it is determined that the key error stratum is the Permian, the geological anomaly causing the error is the reverse fault, and the error range is between the breakpoint of the upper plate breaking through the Longtan Formation and the breakpoint of the lower plate breaking through the Liangshan Formation. T The top of the stratum T delineating the geological anomaly t and the bottom of the formation T b The lateral range of the imaged data volume P is offset in the depth domain D The top of the stratum D in the delineation of the geological anomaly t and the bottom of the formation D b lateral range.

[0056] S3. Delineate the target body’s expected output horizon based on the relationship between the error and the geological anomaly, and calculate the target body’s shape variable

[0057] Migrate the imaging data volume P in the depth domain D The target layer H is picked up in the depth domain; the direction and scale of the target depth change caused by the geological anomaly are deduced according to the relationship between the well-seismic error and the thickness of the geological anomaly, and the target expected output layer H is further outlined in the depth domain migration imaging data volume. * , use the following formula to calculate the target shape variable △H:

[0058] △H=H * -H

[0059] Where △H is the target shape variable; H * is the expected output layer of the target in the depth domain; H is the layer of the target in the depth domain migration imaging data volume.

[0060] S4. Calculate the velocity disturbance according to the range of the geological anomaly and the target shape variable, generate the time domain velocity ratio body, smooth the velocity ratio body and apply disturbance to the velocity model

[0061] S41. Calculate the velocity disturbance according to the range of the geological anomaly and the target shape. The calculation formula is:

[0062] U=(D b -D t +△H) / (D b -D t )

[0063] Where U is the velocity disturbance; D b D is the stratum bottom of the geological anomaly in the depth domain migration imaging data volume; t is the top of the stratum of the geological anomaly in the depth domain migration imaging data volume; △H is the target body shape variable;

[0064] S42. Generate time domain velocity ratio volume: In the time domain migration imaging data volume, the top of the geological anomaly body T t and the bottom of the formation T b Fill U between the two and fill 1 in the remaining space to generate a time domain velocity proportional volume S T ;

[0065] S43. Smoothed time domain velocity ratio S T Get SS T , and the time domain velocity model V T Apply a perturbation:

[0066] UV T =SS T *VT

[0067] Where, UV T is the time domain velocity model after disturbance; SS T V is the velocity ratio in the time domain after smoothing; T is the time domain velocity model;

[0068] S44. The time domain velocity model UV after disturbance T Convert to the depth domain and obtain the perturbed depth domain velocity model UV D .

[0069] S5. Use the disturbed depth domain velocity model to perform depth migration processing and perform grid tomography inversion to obtain the optimized velocity model

[0070] Use the perturbed depth domain velocity model UV D Perform depth migration processing and perform multiple rounds of grid tomography inversion according to the gather flattening situation until the velocity is stable and the gather is flattened to obtain an optimized velocity model, such as Figure 4 shown.

[0071] Depend on Figure 3 and Figure 4 By comparison, it can be seen that the velocity near the Permian reverse fault (geological anomaly) increases after optimizing the depth domain velocity model.

[0072] S6. Use the optimized velocity model to perform overall depth migration, obtain a new depth domain migration imaging data volume, and monitor whether it is consistent with the horizontal well A while drilling guidance model. The results are as follows: Figure 5 shown.

[0073] Depend on Figure 5 It can be seen that after optimizing the velocity model, the false structure is eliminated and the consistency between well and seismic data is greatly improved.

[0074] A horizontal well B is drilled adjacent to the horizontal well A in the area. The relative positions of well A and well B are as follows: Figure 6 As shown in Figure 2, the consistency between the LWD steering model of horizontal well B and the new depth domain migration imaging data after the optimized velocity model is monitored. The results are shown in Figure 2. Figure 7 shown.

[0075] Depend on Figure 7 It can be seen that all the false structures caused by the same geological anomalies in the area have been eliminated, and the seismic coincidence degree of horizontal well B has reached 100%.

[0076] It can be seen that after optimizing the velocity model, the false structure was eliminated, the well-seismic consistency was greatly improved, and the subsequent drilling of the same well and the full-well drilling of the adjacent well did not encounter the well-seismic error caused by the geological anomaly. This shows that optimizing the velocity model by this method is reasonable and reliable, and can more fully eliminate the target body morphology changes caused by the overlying geological anomaly, thereby effectively improving the well-seismic consistency and enhancing the support effect of seismic data on horizontal well drilling.

[0077] Example 2: A device for analyzing the actual drilling situation of a horizontal well and optimizing the velocity model

[0078] This embodiment discloses a device for analyzing the actual drilling situation of a horizontal well and optimizing a velocity model, comprising:

[0079] A judgment module is used to monitor whether the horizontal well drilling guidance model and the depth domain migration imaging data volume are consistent;

[0080] The geological anomaly analysis module is used to analyze the strata causing the error and define the scope of the geological anomaly when there is a mismatch;

[0081] The target body shape variable calculation module is used to outline the target body's expected output layer according to the relationship between the error and the geological anomaly body, and calculate the target body shape variable;

[0082] The velocity perturbation module is used to calculate the velocity perturbation amount according to the range of the geological anomaly body and the target body shape variable, generate the time domain velocity proportional body, smooth the velocity proportional body, and apply perturbation to the velocity model;

[0083] The velocity model optimization module uses the disturbed velocity model to perform depth migration processing and grid tomography inversion to obtain an optimized velocity model.

Claims

1. A method for analyzing the actual drilling situation of a horizontal well and optimizing a velocity model, characterized in that: The following steps are involved: S1. Monitor whether the horizontal well drilling steering model is consistent with the depth domain migration imaging data volume; S2. When there is a mismatch, analyze the strata causing the error and define the scope of the geological anomaly; S3. Delineate the target body's expected output horizon based on the relationship between the error and the geological anomaly, and calculate the target body's shape variable; S4. Calculate the velocity disturbance amount according to the range of the geological anomaly body and the target body shape variable, generate a time domain velocity proportional body, smooth the velocity proportional body, and apply disturbance to the velocity model; S5. Use the disturbed velocity model to perform depth migration processing and perform grid tomography inversion to obtain the optimized velocity model.

2. The method for analyzing the actual drilling situation of a horizontal well and optimizing the velocity model according to claim 1, characterized in that: The step S2 specifically includes: When a mismatch occurs, the strata causing the error are analyzed by combining plane and section, and the lateral range of the stratigraphic top and stratigraphic bottom of the geological anomaly is delineated in the time domain migration imaging data volume and the depth domain migration imaging data volume.

3. A method for analyzing the actual drilling situation of a horizontal well and optimizing the velocity model according to claim 1 or 2, characterized in that: The step S3 specifically includes: According to the relationship between the error and the thickness of the geological anomaly, the depth change of the target body caused by the geological anomaly is calculated, and the expected output layer H of the target body in the depth domain is outlined. * , and calculate the target shape variable △H: △H=H * -H Where △H is the target shape variable; H * is the expected output layer of the target in the depth domain; H is the layer of the target in the depth domain migration imaging data volume.

4. A method for analyzing the actual drilling situation of a horizontal well and optimizing the velocity model according to claim 1 or 2, characterized in that: The step S4 specifically includes: S41. Calculate the velocity disturbance according to the range of the geological anomaly and the target shape. The calculation formula is: U=(D b -D t +△H) / (D b -D t ) Where U is the velocity disturbance; D b D is the stratum bottom of the geological anomaly in the depth domain migration imaging data volume; t is the top of the stratum of the geological anomaly in the depth domain migration imaging data volume; △H is the target body shape variable; S42. Generate time domain velocity ratio volume: In the time domain migration imaging data volume, the top of the geological anomaly body T t and the bottom of the formation T b Fill U between the two and fill 1 in the remaining space to generate a time domain velocity proportional volume S T ; S43. Smoothed time domain velocity ratio S T Get SS T , and the time domain velocity model V T Apply a perturbation: UV T =SS T *V T Where, UV T is the time domain velocity model after disturbance; SS T V is the velocity ratio in the time domain after smoothing; T is the time domain velocity model; S44. The time domain velocity model UV after disturbance T Convert to the depth domain and obtain the perturbed depth domain velocity model UV D .

5. A method for analyzing the actual drilling situation of a horizontal well and optimizing the velocity model according to claim 1 or 2, characterized in that: The step S5 specifically includes: The disturbed depth domain velocity model is used for migration and multiple rounds of grid tomography inversion are performed until the velocity is stable and the gathers are flattened, thus obtaining the optimized velocity model.

6. A method for analyzing the actual drilling situation of a horizontal well and optimizing the velocity model according to claim 1 or 2, characterized in that: The step S5 further includes: S6. Use the optimized velocity model to perform overall depth migration, obtain a new depth domain migration imaging data volume, and monitor whether it is consistent with the horizontal well drilling guidance model.

7. A device for analyzing the actual drilling situation of a horizontal well and optimizing the velocity model, characterized in that: include: A judgment module is used to monitor whether the horizontal well drilling guidance model and the depth domain migration imaging data volume are consistent; The geological anomaly analysis module is used to analyze the strata causing the error and define the scope of the geological anomaly when there is a mismatch; The target body shape variable calculation module is used to outline the target body's expected output layer according to the relationship between the error and the geological anomaly body, and calculate the target body shape variable; The velocity perturbation module is used to calculate the velocity perturbation amount according to the range of the geological anomaly body and the target body shape variable, generate the time domain velocity proportional body, smooth the velocity proportional body, and apply perturbation to the velocity model; The velocity model optimization module uses the disturbed velocity model to perform depth migration processing and grid tomography inversion to obtain an optimized velocity model.

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