Method and equipment for dynamically predicting key parameters of shale gas horizontal well target body and storage medium

Abstract

The invention discloses a method and equipment for dynamically predicting key parameters of a shale gas horizontal well target body and a storage medium, and belongs to the technical field of oil and gas seismic exploration. The method mainly comprises the following steps of: reading dynamically-changed actual drilling information of the horizontal well, and dynamically adjusting seismic data according to the actual drilling information of the horizontal well to obtain a real-time prediction result of key parameters of a target body. According to the method, the parameter accuracy of dynamic prediction is high, the function of predicting the parameters of other horizontal well target bodies on the same platform and the adjacent platform can be achieved, the depth of a target entering point can be predicted more accurately, and the form and the dip angle of a target body target are reasonably judged; abnormal factors existing in the horizontal well drilling section can be accurately predicted, and risk early warning is provided for engineering construction links such as well drilling; key parameters of the target body in the target area can be updated in time, drilling guidance is assisted, the drilling rate of the horizontal well is increased, the shale gas development effect is improved, and the method is suitable for horizontal well prediction in shale gas development.

Description

Technical Field

[0001] This invention belongs to the field of seismic exploration technology for oil and gas, and relates to a method for predicting target bodies in shale gas horizontal wells. Specifically, it relates to a method, equipment, and storage medium for dynamically predicting key parameters of target bodies in shale gas horizontal wells. Background Technology

[0002] Marine shale is currently the most important stratum for shale gas development, characterized by "one thinness (thin 'platinum target' thickness), two lows (low porosity, low permeability), three highs (high temperature, high stress, high stress difference), and four developments (development of small faults, micro-structures, fractures, and bedding)." As development progresses, underground geological conditions become more complex, increasing the difficulty of horizontal drilling, fracturing, and other engineering operations.

[0003] 3D seismic data offers the advantage of continuous spatial sampling, enabling prediction of subsurface conditions. However, previous seismic data interpretation results have primarily been applied to exploration site selection, well location deployment, and drilling design, constituting "static prediction" (according to Yang Qinyong et al., *Shale Gas Geophysical Technology*, published by China Petrochemical Press, 2018). Shale gas development mainly employs horizontal drilling, where the drill bit's movement within the target body is a dynamic process. This inevitably leads to discrepancies between actual subsurface conditions and pre-drilling static seismic predictions. For seismic prediction to provide forward-looking guidance in horizontal drilling, rapid dynamic prediction is essential.

[0004] Horizontal well targets contain a wealth of information, primarily in the form of drilling guidance results and logging-while-drilling data. This differs from seismic prediction. Effectively extracting key information from the drilling process and applying it to seismic prediction, thereby achieving dynamic and timely seismic prediction, are pressing issues that need to be addressed. Summary of the Invention

[0005] The purpose of this invention is to provide a method, device, and storage medium for dynamically predicting key parameters of target bodies in shale gas horizontal wells, in order to solve the problems of current seismic prediction methods being unable to be dynamically adjusted and lacking predictive foresight during horizontal drilling.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows: A method for dynamically predicting key parameters of a target body in a shale gas horizontal well includes the following steps: S1. Select the target area for dynamic prediction. Based on the principle of being able to completely predict the trajectory of all horizontal wells of the platform and also predict the trajectory of adjacent platforms, set the coordinate range of the target area. S2. Obtain the first round of earthquake data for the target area; S3. Obtain drilling data for the vertical section of the horizontal well and mark the drilled formation interface on the first round of seismic data; S4. Determine whether the depth of the actual drilled stratum interface matches the depth predicted by the first round of seismic data: if they match, proceed to step S6; if they do not match, proceed to step S5. S5. Dynamically adjust the first round of earthquake data, update the time-depth-velocity field of the target area, and form the second round of earthquake data; S6. Obtain well trajectory data and geological steering model of the horizontal section of the horizontal well, vectorize the geological steering model, pick the actual drilled landmark stratigraphic interface, and set dynamic control points at intervals of 20-50m; S7. Adjust the time-depth relationship of the dynamic control points so that the landmark stratigraphic interface predicted by the seismic data matches the actual drilled landmark stratigraphic interface, update the time-depth velocity field of the target area, perform anisotropic pre-stack depth migration processing, and form the third round of seismic data. S8. Repeat steps S6 and S7 until drilling is complete, to generate the Nth round of seismic data; S9. Based on the drilling completion information, update the relevant parameters to obtain the updated seismic inversion data and the updated fracture prediction data, and then complete the dynamic prediction of the key parameters of the target body of the shale gas horizontal well.

[0007] As a limitation, the term "match" means that the absolute value of the difference between the two is less than or equal to 2m.

[0008] As another limitation, the seismic data includes seismic depth domain data, stratigraphic and fault interpretation data; the drilling data includes well trajectory data and formation interface depth values.

[0009] As a further limitation, the well trajectory data is converted into X and Y coordinates using the minimum curvature method.

[0010] As a further limitation, it also includes: S10. Repeat steps S1-S9 until all horizontal wells in the target area are drilled.

[0011] The present invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-described method for dynamically predicting key parameters of a target body in a shale gas horizontal well.

[0012] The present invention also provides a computer-readable storage medium storing a computer program for performing the above-described method for dynamically predicting key parameters of a target body in a shale gas horizontal well.

[0013] By adopting the above technical solution, the technical progress achieved by this invention compared with the prior art is as follows: This invention provides a method, equipment, and storage medium for dynamically predicting key parameters of target bodies in shale gas horizontal wells. The dynamically predicted parameters have high accuracy and can predict the target body parameters of other horizontal wells on the same and adjacent platforms. Application of this method to over 200 horizontal wells in a certain work area has demonstrated that it can more accurately predict the depth of the entry point, reasonably determine the shape and dip angle of the target body, and improve the average consistency rate between the occurrence prediction and the actual drilling prediction from 89% to 99%. It can also accurately predict abnormal factors existing in the horizontal drilling section, providing risk warnings for drilling and other engineering construction stages. Furthermore, it can update the key parameters of the target body in the target area in a timely manner, assisting in drilling guidance, thereby improving the drilling encounter rate of horizontal wells and enhancing the shale gas development effect. The average drilling encounter rate of horizontal wells in shale gas structurally complex areas has increased from 60% to 73%, and the average drilling encounter rate of horizontal wells in structurally gentle areas has increased from 89% to 99%. Attached Figure Description

[0014] Figure 1 This is a flowchart of the method in Example 1; Figure 2 This is a diagram showing the predicted depth, orientation, and dip angle of the well target in Example 1. Figure 3 This is a schematic diagram of risk prediction for the horizontal section of the well in Example 1. Detailed Implementation

[0015] The present invention will be further described in detail below through specific embodiments. It should be understood that the described embodiments are only for explaining the present invention and do not limit the present invention.

[0016] Example 1 This embodiment discloses a method for dynamically predicting key parameters of target bodies in shale gas horizontal wells. The method was applied in a shale gas development area with over 200 horizontal wells. The flowchart of the method is shown below. Figure 1 As shown, the specific steps include the following sequential steps: S1. Select the target area range for dynamic prediction. Based on the platform coordinates and designed well trajectories of the shale gas horizontal wells, and in accordance with the principle of being able to completely predict the trajectories of all horizontal wells on the platform and to predict the trajectories of adjacent platforms, set the coordinate range of the target area. S2. Obtain the first round of earthquake data for the target area, including earthquake depth domain data, stratigraphic and fault interpretation data; S3. Obtain drilling data for the vertical section of the horizontal well, including well trajectory data and formation interface depth values ​​(which can be obtained from logging or well logging results), and mark the drilled formation interface on the first round of seismic data; S4. Read the difference between the depth of the actual drilled stratum interface and the depth predicted by the first round of seismic data from shallow to deep, and determine whether the depth of the actual drilled stratum interface matches the depth predicted by the first round of seismic data: if the absolute value of the difference between the two is less than or equal to 2m, then the stratum interface is not adjusted and proceed to step S6; if the absolute value of the difference between the two is greater than 2m, then proceed to step S5. S5. Dynamically adjust the first round of seismic data. Based on the stratigraphic stratification and logging curves of the vertical well section, update the time-depth velocity field of the target area and dynamically update the seismic depth domain data to form the second round of seismic data. S6. After drilling into the target body, acquire well trajectory data of the horizontal section of the horizontal well, as well as the synchronously updated geological steering model of the horizontal well (usually in image form). Well trajectory data typically includes measurement depth, dip angle, azimuth angle, etc., which need to be converted into X and Y coordinates, or horizontal displacement and closed azimuth using the minimum curvature method; The horizontal displacement on the geological steering model is set as the abscissa and the elevation and depth are set as the ordinate. The geological steering model is vectorized, and the actual drilling landmark stratigraphic interface in the image is picked out. Dynamic control points are set at intervals of 20-50m (based on the intensity of well trajectory fluctuations). S7. Based on the elevation of the actual drilled landmark stratigraphic interface of each dynamic control point, adjust the time-depth relationship of the dynamic control points so that the landmark stratigraphic interface predicted by the seismic data matches the actual drilled landmark stratigraphic interface (the absolute value of the difference between the two is less than or equal to 2m), update the time-depth velocity field of the target area, and perform anisotropic pre-stack depth migration processing on the seismic data of the target area based on TTI medium to form the third round of seismic data. S8. Repeat steps S6 and S7 until drilling is complete, to generate the Nth round of seismic data; S9. Update relevant parameters based on the drilling completion information (parameters of the actual drilled formation, mainly including formation depth, formation attitude, reservoir parameters, fracture development, etc.), perform seismic inversion, and obtain updated seismic inversion data; compare the consistency between the first round of fracture prediction data and the actual drilled fracture situation. If they do not match, adjust the parameters in the fracture prediction method to make them more consistent with the actual drilling results, and obtain updated fracture prediction data. S10. Using the Nth round of seismic data, updated seismic inversion data, and updated fracture prediction data generated after the completion of the first horizontal well in the target area, apply them to the next well in the target area, providing suggestions for its drilling design, fracturing design, etc., and predicting the well target depth, attitude, and dip angle as follows: Figure 2 As shown, the risk prediction for the horizontal section of the well is as follows: Figure 3 As shown; Depend on Figure 2It can be seen that this method can more accurately predict the shape and dip angle of the target, and the average agreement rate between the predicted attitude and the actual drilling prediction has increased from 89% to 99%; Figure 3 It can be seen that this method can accurately predict abnormal factors in horizontal drilling sections and provide risk warnings for drilling and other engineering construction processes. After the next well is started, steps S1-S9 are repeated until all horizontal wells in the target area are drilled. This method can update the key parameters of the target body in the target area in a timely manner, help guide the drilling, thereby improving the drilling rate of horizontal wells and enhancing the development effect of shale gas. In this region, the average drilling rate of horizontal wells in shale gas complex areas has increased from 60% to 73%, and the average drilling rate of horizontal wells in gently sloping areas has increased from 89% to 99%.

[0017] Example 2 This embodiment provides a computer device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, to implement the above-mentioned method for dynamically predicting key parameters of the target body of a shale gas horizontal well.

[0018] This memory is used to store non-transitory computer-readable instructions. Specifically, the memory may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may, for example, include random access memory (RAM) and / or cache memory. The non-volatile memory may, for example, include read-only memory (ROM), hard disk, flash memory, etc.

[0019] The processor may be a central processing unit (CPU) or other form of processing unit with data processing and / or instruction execution capabilities, and may control other components in the electronic device to perform desired functions. The processor is used to execute computer-readable instructions stored in the memory.

[0020] Those skilled in the art will understand that, in order to solve the technical problem of how to achieve a good user experience, this embodiment may also include well-known structures such as communication buses and interfaces, and these well-known structures should also be included within the protection scope of this disclosure.

[0021] For a detailed description of this embodiment, please refer to the corresponding descriptions in the foregoing embodiments, which will not be repeated here.

[0022] Example 3 This embodiment provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method for dynamically predicting key parameters of a target body in a shale gas horizontal well.

[0023] The computer-readable storage medium stores non-transitory computer-readable instructions thereon. When the non-transitory computer-readable instructions are executed by a processor, all or part of the steps of the methods of the foregoing embodiments are performed.

[0024] The aforementioned computer-readable storage media include, but are not limited to: optical storage media (e.g., CD-ROM and DVD), magneto-optical storage media (e.g., MO), magnetic storage media (e.g., magnetic tape or portable hard drive), media with built-in rewritable non-volatile memory (e.g., memory card), and media with built-in ROM (e.g., ROM cartridge).

Claims

1. A method for dynamically predicting key parameters of a target body in a shale gas horizontal well, characterized in that, Includes the following steps: S1. Select the target area for dynamic prediction. Based on the principle of being able to completely predict the trajectory of all horizontal wells of the platform and also predict the trajectory of adjacent platforms, set the coordinate range of the target area. S2. Obtain the first round of earthquake data for the target area; S3. Obtain drilling data for the vertical section of the horizontal well and mark the drilled formation interface on the first round of seismic data; S4. Determine whether the depth of the actual drilled stratum interface matches the depth predicted by the first round of seismic data: if they match, proceed to step S6; if they do not match, proceed to step S5. S5. Dynamically adjust the first round of earthquake data, update the time-depth-velocity field of the target area, and form the second round of earthquake data; S6. Obtain well trajectory data and geological steering model of the horizontal section of the horizontal well, vectorize the geological steering model, pick the actual drilled landmark stratigraphic interface, and set dynamic control points at intervals of 20-50m; S7. Adjust the time-depth relationship of the dynamic control points so that the landmark stratigraphic interface predicted by the seismic data matches the actual drilled landmark stratigraphic interface, update the time-depth velocity field of the target area, perform anisotropic pre-stack depth migration processing, and form the third round of seismic data. S8. Repeat steps S6 and S7 until drilling is complete, to generate the Nth round of seismic data; S9. Based on the drilling completion information, update the relevant parameters to obtain the updated seismic inversion data and the updated fracture prediction data, and then complete the dynamic prediction of the key parameters of the target body of the shale gas horizontal well.

2. The method for dynamically predicting key parameters of a target body in a shale gas horizontal well according to claim 1, characterized in that, The term "match" refers to a situation where the absolute value of the difference between the two is less than or equal to 2m.

3. A method for dynamically predicting key parameters of a target body in a shale gas horizontal well according to claim 1 or 2, characterized in that, The seismic data includes seismic depth domain data, stratigraphic and fault interpretation data; the drilling data includes well trajectory data and formation interface depth values.

4. The method for dynamically predicting key parameters of a target body in a shale gas horizontal well according to claim 3, characterized in that, The well trajectory data was converted into X and Y coordinates using the minimum curvature method.

5. The method for dynamically predicting key parameters of a target body in a shale gas horizontal well according to claim 4, characterized in that, Also includes: S10. Repeat steps S1-S9 until all horizontal wells in the target area have been drilled.

6. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method for dynamically predicting key parameters of the target body of a shale gas horizontal well as described in any one of claims 1-5.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that performs the method for dynamically predicting key parameters of a target body in a shale gas horizontal well as described in any one of claims 1-5.

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