Geological guidance methods, devices, terminals, and media based on seismic data reconstruction

Abstract

This invention discloses a geological guidance method, device, terminal, and medium based on seismic data reconstruction, including: determining regional data; constructing a fine geological framework network model; resampling to assign seismic attribute values ​​to a three-dimensional geological grid space; obtaining geostatistical parameters; simulating seismic amplitude values ​​in the three-dimensional geological grid space; converting the three-dimensional seismic amplitude attribute model into a three-dimensional seismic data volume; using the three-dimensional seismic data volume as a physical constraint to construct a fine horizontal well geological guidance model; and providing geological guidance for the drilling process through the fine horizontal well geological guidance model. This invention, by constructing a fine geological framework network model and utilizing the seismic information contained in two-dimensional seismic data to reconstruct a three-dimensional seismic data volume, taps into the usability of two-dimensional seismic data, constructs a fine horizontal well geological guidance model, and provides geological guidance for the drilling process through the fine horizontal well geological guidance model, thereby improving drilling success rate and reducing drilling risks.

Description

Technical Field

[0001] This invention relates to the field of geological steering decision-making technology for horizontal wells in oil exploration, specifically to a geological steering method, device, terminal, and medium based on seismic data reconstruction. Background Technology

[0002] Geological-guided modeling is a key technology in geological-guided methods, and it mainly includes geological structure modeling and stratigraphic property modeling.

[0003] In conventional modeling methods, structural modeling often uses a three-dimensional geological framework model to construct the structural undulations in the horizontal well orientation, while the changes in stratigraphic properties in this orientation are predicted using three-dimensional seismic data volumes, thereby establishing a geological steering model that closely approximates the actual situation.

[0004] In actual production, by tracking the formation structure location and physical property changes of the actual drilled well trajectory in the model in real time, scientific and reasonable suggestions can be made for the next drilling decision-making plan in a timely manner to avoid possible mistakes in the drilling project.

[0005] However, in some complex surface environments (such as piedmont zones and steep structural zones), the harsh surface conditions make it impossible to conduct on-site acquisition of 3D seismic data, necessitating 2D seismic exploration. With only 2D seismic data available, drilling of horizontal process wells requires using this data for stratigraphic modeling and stratigraphic property prediction. However, the spacing between 2D seismic lines is typically large, leading to significant errors in predicting stratigraphic morphology and property distribution. This results in limited data for constructing geological steering models, leading to poor accuracy. Relying on such models for geological steering drilling decisions can easily result in drilling failure. Summary of the Invention

[0006] The technical problem to be solved by this invention is that when only two-dimensional seismic data is available, the geological guidance model has limited basis for construction and poor accuracy. If geological guidance drilling decisions are made based on this model, it is easy to cause drilling failure. The purpose is to provide a geological guidance method, device, terminal and medium based on seismic data reconstruction, which solves the drilling guidance decision problem when only two-dimensional seismic data is available.

[0007] This invention is achieved through the following technical solution:

[0008] Firstly, a geological guidance method based on seismic data reconstruction includes:

[0009] Determine the region's two-dimensional seismic data, well logging data, well logging data, and seismic interpretation horizon data;

[0010] Construct a refined geological framework network model;

[0011] Two-dimensional seismic data are resampled in a fine geological framework network model to assign seismic attribute values ​​to the three-dimensional geological grid space;

[0012] Based on the regional geological sedimentary patterns and by analyzing the statistical patterns of seismic attribute values ​​in various strata, geostatistical parameters were obtained.

[0013] Using resampled two-dimensional seismic data as hard data and geostatistical parameters as trend constraints, the seismic amplitude values ​​in three-dimensional geological grid space are simulated through a stochastic simulation algorithm.

[0014] A three-dimensional seismic amplitude attribute model is constructed based on seismic attribute values, and the three-dimensional seismic amplitude attribute model is transformed into a three-dimensional seismic data volume through simulation perturbation algorithm and seismic amplitude values;

[0015] Using 3D seismic data volumes as physical constraints, a refined geological steering model for horizontal wells is constructed.

[0016] Geological guidance is provided for the drilling process using a refined horizontal well geological steering model.

[0017] Specifically, the method for constructing a refined geological framework network model includes:

[0018] By integrating well logging data and well logging data, optimizing the velocity field, and adjusting the seismic interpretation horizon, the seismic interpretation horizon data is matched with the actual drilling results, with the ultimate goal of increasing the matching degree.

[0019] Set the target well accuracy requirements and divide the horizontal modeling grid on the horizontal plane;

[0020] By performing well-to-well interpolation using seismic interpretation of stratigraphic data, a finely modeled three-dimensional structural surface is obtained;

[0021] Vertical modeling meshes are divided on the longitudinal plane to establish multiple three-dimensional structural surfaces, thereby obtaining a fine geological framework network model.

[0022] Optionally, the statistical regularity is obtained through a probability distribution function and a variation function;

[0023] The distribution characteristics of earthquake amplitude values ​​in three-dimensional space are obtained by using probability distribution functions, and the three-dimensional normal distribution curve of earthquake amplitude values ​​is determined.

[0024] By using the variogram function, the parameters of the variogram function are set according to the magnitude, frequency, and phase changes of the earthquake amplitude, and the spatial positional relationship and correlation between the earthquake amplitudes of unknown points and known points are obtained.

[0025] Specifically, the methods of using the probability distribution function include:

[0026] The range of the normal distribution of earthquake amplitude values ​​was statistically analyzed, and the corresponding normal distribution characteristics were determined.

[0027] Using the normal distribution characteristics as a trend constraint, a three-dimensional normal distribution curve of earthquake amplitude values ​​is simulated;

[0028] The mathematical expression for the variation function is:

[0029]

[0030] In the formula, N(h) represents the number of points with a distance of h, where h represents the distance input when calculating spatial correlation, and Z(x) represents the distance input when calculating spatial correlation. i Let Z(x) represent a random function, and let Z(x) be the difference function. i )-Z(x i The first and second moments of (+h) depend only on h;

[0031] The range, sill value, and nugget value are determined by the variogram function, where the range is the h value when r(h) reaches a stationary value, the sill value is the r(h) value when r(h) reaches a stationary value, and the nugget value is the non-zero r(h) value when h = 0.

[0032] Optionally, the random simulation algorithm is a truncated Gaussian simulation algorithm or an indicator Kriging simulation algorithm.

[0033] Specifically, methods for geological steering the drilling process using a refined horizontal well geological steering model include:

[0034] Drill the well and perform forward modeling of the horizontal well profile. Determine whether the measurement-while-drilling (MWD) wellbore conforms to the refined horizontal well geological steering model. If they do not conform, modify the refined horizontal well geological steering model; if they conform, then:

[0035] Determine whether the wellbore trajectory passes through the sweet spot required by the geological design, and whether the subsequent trajectory is parallel to the undulation of the formation. If not, adjust the drilling trajectory; if so, continue drilling.

[0036] Secondly, a geological guidance device based on seismic data reconstruction includes:

[0037] The determination module is used to determine the two-dimensional seismic data, well logging data, well logging data, and seismic interpretation horizon data of the region;

[0038] The first modeling module is used to construct a fine geological framework network model;

[0039] The assignment module is used to resample two-dimensional seismic data in a fine geological framework network model and assign seismic attribute values ​​to the three-dimensional geological grid space.

[0040] The analysis module is used to obtain geostatistical parameters by analyzing the statistical regularities of seismic attribute values ​​of various strata based on regional geological sedimentary patterns.

[0041] The simulation module is used to simulate the earthquake amplitude values ​​in a three-dimensional geological grid space using resampled two-dimensional seismic data as hard data and geostatistical parameters as trend constraints, through a stochastic simulation algorithm.

[0042] The reconstruction module is used to construct a three-dimensional seismic amplitude attribute model based on seismic attribute values, and to convert the three-dimensional seismic amplitude attribute model into a three-dimensional seismic data volume through simulation perturbation algorithm and seismic amplitude values;

[0043] The second modeling module is used to construct a fine-grained geological steering model of a horizontal well by using the three-dimensional seismic data volume as a physical constraint.

[0044] The guidance module is used to guide the drilling process geologically using a fine horizontal well geological guidance model.

[0045] Specifically, the first modeling module includes:

[0046] The matching module is used to optimize the velocity field and adjust the seismic interpretation horizon by integrating well logging data and well logging data, so that the seismic interpretation horizon data matches the actual drilling results, with the ultimate goal of increasing the matching degree.

[0047] The first partitioning module is used to partition a horizontal modeling grid on a horizontal plane according to the set target well accuracy requirements;

[0048] The interpolation module is used to perform inter-well interpolation using seismic interpretation layer data to obtain finely modeled 3D structural surfaces;

[0049] The second partitioning module is used to partition the vertical modeling mesh on the longitudinal plane, establish multiple three-dimensional structural surfaces, and obtain a fine geological framework network model.

[0050] The guidance module includes:

[0051] The first judgment module is used to perform forward modeling of horizontal well curves during drilling and to determine whether the measurement-while-drilling wellbore is consistent with the fine horizontal well geological steering model.

[0052] The correction module is used to correct the fine horizontal well geological steering model when the first judgment module determines that the model does not match.

[0053] The second judgment module is used to determine whether the wellbore trajectory passes through the sweet spot required by the geological design when the first judgment module judges the composite, and whether the subsequent trajectory is parallel to the undulation of the formation structure.

[0054] The control module is used to adjust the drilling trajectory when the second judgment module determines that it is not true, and to control the drill bit to drill forward when the second judgment module determines that it is true.

[0055] Thirdly, a geological guidance terminal based on seismic data reconstruction includes a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor, when executing the computer program, implements the steps of the geological guidance method based on seismic data reconstruction as described above.

[0056] Fourthly, a computer-readable storage medium storing a computer program, characterized in that, when executed by a processor, the computer program implements the steps of the geological guidance method based on seismic data reconstruction as described above.

[0057] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0058] This invention constructs a fine geological framework network model and reconstructs existing two-dimensional seismic data. By utilizing the seismic information contained in the two-dimensional seismic data, it reconstructs a three-dimensional seismic data volume, tapping the potential of two-dimensional seismic data. It then constructs a fine horizontal well geological steering model and uses this model to provide geological guidance for the drilling process, thereby improving drilling success rate and reducing drilling risks. Attached Figure Description

[0059] The accompanying drawings illustrate exemplary embodiments of the present invention and, together with the description thereof, serve to explain the principles of the invention. These drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, but do not constitute a limitation on the embodiments of the present invention.

[0060] Figure 1 This is a flowchart illustrating the geological guidance method based on seismic data reconstruction according to the present invention.

[0061] Figure 2 This is a schematic diagram showing the orientation of the horizontal wellbore trajectory perpendicular to the two-dimensional survey line in a project example according to the present invention.

[0062] Figure 3 It is the projection of the wellbore trajectory onto a two-dimensional seismic profile as described in the project example according to the present invention.

[0063] Figure 4 It is a conventional geological guidance model as described in the project example according to the present invention.

[0064] Figure 5 This is a schematic diagram showing the orientation of the reconstructed horizontal wellbore trajectory parallel to the two-dimensional survey line according to the present invention.

[0065] Figure 6 It is a seismic profile along the well trajectory after three-dimensional seismic reconstruction according to the present invention.

[0066] Figure 7 It is the pre-drilling geological guidance model according to the present invention.

[0067] Figure 8 The geological steering model for completed drilling as described in this invention Detailed Implementation

[0068] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of the invention.

[0069] It should also be noted that, for ease of description, only the parts relevant to the present invention are shown in the accompanying drawings.

[0070] Where there is no conflict, the embodiments and features described herein can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0071] Project Examples

[0072] In some areas with complex environments, where high mountains obstruct the drilling site, existing equipment cannot meet the needs of 3D seismic acquisition, and only 2D seismic acquisition has been carried out. With only 2D seismic data available, conducting horizontal well drilling targeting specific gas-bearing formations has encountered considerable difficulties.

[0073] First, according to the requirements of the preliminary gas layer fine evaluation work, the horizontal well trajectory needs to be controlled within a 10m box, with a vertical depth of approximately 3000m. Second, the drilling azimuth of this horizontal well is perpendicular to the two-dimensional seismic survey line, and the horizontal wellbore trajectory is located precisely between two seismic survey lines, with a relatively large distance between the survey lines. Figure 2 As shown. Figure 3 This is the projection of the horizontal well trajectory onto the AA' 2D seismic profile (construction acquisition data). In this figure, because the horizontal well trajectory is almost parallel to the survey line, its projected trajectory is severely distorted, making it impossible to make a scientific and reasonable judgment and prediction on the geological structure and changes in geological properties encountered during drilling. Figure 4 It is a geological steering model constructed using only two-dimensional seismic data and adjacent well data. This model deviates significantly from the actual well drilling conditions and is difficult to meet the needs of real-time geological steering decision-making.

[0074] To address the above situation, the following embodiments are provided:

[0075] Example 1

[0076] This embodiment provides a geological guidance method based on seismic data reconstruction, such as... Figure 1 As shown, the method includes:

[0077] The first step is to determine the region's 2D seismic data, well logging data, well logging data, and seismic interpretation horizon data; the data is acquired in real time using existing 2D seismic acquisition equipment, drilling equipment, etc.

[0078] The second step involves constructing a refined geological framework network model; the methods include:

[0079] a) Optimize the velocity field by integrating well logging data and well logging data, and fine-tune the seismic interpretation horizon to make the seismic interpretation horizon data match the actual drilling results, with the ultimate goal of increasing the matching degree; that is, to make the seismic interpretation horizon data match the actual drilling results as perfectly as possible.

[0080] b) Horizontal meshing: Set the target well accuracy requirements and divide the horizontal modeling mesh on the horizontal plane. That is, according to the set target well accuracy, divide the mesh on the plane. In this embodiment, the surface element is generally 25m×25m in size.

[0081] c) Interpolation modeling: Inter-well interpolation is performed using seismic interpretation layer data to obtain a finely modeled three-dimensional structural surface; during the interpolation process, well logging data recorded in the drilled wells and layered data from the integrated well logging interpretation are used to constrain and control the interpretation layers.

[0082] d) Vertical meshing: Divide the vertical plane into vertical modeling meshes, establish multiple three-dimensional structural surfaces, and obtain a fine geological framework network model.

[0083] The third step is to resample the two-dimensional seismic data in the fine geological framework network model and assign seismic attribute values ​​to the three-dimensional geological grid space. During the resampling operation, attention should be paid to the reasonable selection of time intervals to ensure that the resampled data (especially for the main research layer) meets the requirement of the highest resolution information to be safely reconstructed, so as to facilitate interpolation calculations in the later stage.

[0084] The fourth step is to obtain the geological sedimentary patterns of the region based on the geological data, and to analyze the statistical patterns (probability distribution function PDF and variogram) of the seismic attribute values ​​of each stratum based on the regional geological sedimentary patterns, in order to obtain the geological statistical parameters.

[0085] The statistical laws are obtained through probability distribution functions and variation functions;

[0086] The distribution characteristics of earthquake amplitude values ​​in three-dimensional space are obtained by using probability distribution functions, and the three-dimensional normal distribution curve of earthquake amplitude values ​​is determined.

[0087] For any real number x, the probability of the event [X < x] is of course a function of x. Let F(x) = P(X < x). Obviously, F(-∞) = 0 and F(∞) = 1. F(x) is called the distribution function of the random variable X. Therefore, the distribution function F(x) completely determines the probability of the event [a ≤ X ≤ b], or rather, the distribution function F(x) completely describes the statistical characteristics of the random variable X. The probability distribution function satisfies the normal distribution characteristics. Before simulation, first statistically analyze the normal distribution range of the seismic amplitude values and determine the corresponding normal distribution characteristics, and use this normal distribution characteristic as a trend constraint condition. The probability distribution characteristics of the seismic amplitude after simulation should also satisfy the normal distribution characteristics before simulation.

[0088] Through the variogram, set the variogram parameters according to the magnitude, frequency, and phase changes of the seismic amplitude values, and obtain the spatial position relationship and correlation between the seismic amplitudes of the unknown points and the known points.

[0089] The mathematical expression of the said variogram is:

[0090]

[0091] In the formula, N(h) represents the number of distances of h, h represents the lag distance (the distance along the grid direction of concern, that is, the input distance when calculating spatial correlation), Z(xi) represents a random function, and the first-order moment and second-order moment of the difference function Z(x i ) - Z(x i +h) only depend on the difference h between the points x i and x i +h (that is, Z(x i ) is second-order stationary or satisfies the intrinsic hypothesis)

[0092] Determine the range, sill value, and nugget value through the variogram. The range is the h value when r(h) reaches the stationary value, the sill value is the r(h) value when r(h) reaches the stationary value, and the nugget value is the non-zero r(h) value when h = 0. In theory, when h = 0, r(h) = 0, but in fact, there will also be a nugget value. There are many reasons for this phenomenon, which may be caused by sampling and experimental errors or small-scale variations.

[0093] In the fifth step, use the resampled two-dimensional seismic data as hard data and the geostatistical parameters as trend constraint conditions, and simulate the seismic amplitude values in the three-dimensional geological grid space through a stochastic simulation algorithm; the stochastic simulation algorithm is the truncated Gaussian simulation algorithm or the indicator Kriging simulation algorithm.

[0094] In the sixth step, construct a three-dimensional seismic amplitude attribute model based on the seismic attribute values, and transform the three-dimensional seismic amplitude attribute model into a three-dimensional seismic data volume through a simulation perturbation algorithm and the seismic amplitude values.

[0095] The seventh step is to use the 3D seismic data volume as a physical constraint to construct a refined horizontal well geological steering model;

[0096] The eighth step is to provide geological guidance for the drilling process using a refined horizontal well geological steering model.

[0097] Example 2

[0098] This embodiment is a further refinement of step eight of embodiment one. The method for geological steering the drilling process using a fine horizontal well geological steering model includes:

[0099] Drilling is performed, and forward modeling of horizontal well curves is conducted. It is also determined whether the measurement-while-drilling wellbore is consistent with the fine horizontal well geological steering model. Drilling-related parameters are obtained in real time through drilling equipment.

[0100] If the model does not match, then revise the fine horizontal well geological steering model;

[0101] If the conditions are met, then it is determined whether the drilling trajectory is appropriate (geologically, the bottom of the well and the subsequent design trajectory should be located in the sweet spot required by the geological design and parallel to the structural undulations; in drilling engineering, the subsequent trajectory should be smooth and require few adjustments).

[0102] This involves determining whether the drilling trajectory meets geological requirements, specifically whether the wellbore trajectory passes through the sweet spot required by the geological design, and whether the subsequent trajectory is parallel to the undulations of the formation. In terms of drilling engineering, the subsequent trajectory should be adjusted to reduce the number of adjustments and lower the risk of drilling operations. If it is suitable, then drilling can proceed.

[0103] If it is not suitable, adjust the drilling trajectory; if it is suitable, drill forward.

[0104] During the drilling process, a cross-section is cut along the wellbore trajectory, and the actual drilling seismic well trajectory is projected onto the seismic profile in real time. The trend of seismic wave amplitude changes at the wellbore trajectory location is compared to predict the undulation of the formation structure and the changes in reservoir properties, so as to make scientific and reasonable drilling decisions, improve the drilling success rate, and reduce drilling risks.

[0105] Example 3

[0106] This embodiment provides a specific implementation project. Embodiment 3 is to perform geological guidance on the area in the project example.

[0107] After following the method in Example 1, the three-dimensional seismic data volume of the region was reconstructed, and under the constraints of the three-dimensional seismic data volume, a fine horizontal well geological steering model was obtained, and drilling was carried out according to the method in Example 2.

[0108] Figure 5 The wellbore trajectory of the horizontal well is parallel to the two-dimensional survey line. Figure 6 This is the projection of the horizontal wellbore trajectory onto the BB' seismic profile (reconstructed data) after reconstructing a 3D seismic data volume from 2D seismic data. In this figure, the profile morphology clearly demonstrates the variations in formation structure and properties along the actual drilled wellbore trajectory. Figure 7 It is an accurate geological steering model based on the constraint reconstruction of the three-dimensional seismic volume. In the actual geological steering process, the geological steering model is mainly referenced by the reconstructed three-dimensional seismic data volume and combined with the measurement while drilling data to fine-tune the geological steering model, locate the formation position of the wellbore trajectory, and make scientific and reasonable decisions for the next drilling step. Figure 8 It is a post-drilling geological steering model, which is not much different from the geological steering model created before drilling.

[0109] Example 4

[0110] This embodiment describes a geological guidance device based on seismic data reconstruction, comprising:

[0111] The determination module is used to determine the two-dimensional seismic data, well logging data, well logging data, and seismic interpretation horizon data of the region;

[0112] The first modeling module is used to construct a fine geological framework network model;

[0113] The assignment module is used to resample two-dimensional seismic data in a fine geological framework network model and assign seismic attribute values ​​to the three-dimensional geological grid space.

[0114] The analysis module is used to obtain geostatistical parameters by analyzing the statistical regularities of seismic attribute values ​​of various strata based on regional geological sedimentary patterns.

[0115] The simulation module is used to simulate the earthquake amplitude values ​​in a three-dimensional geological grid space using resampled two-dimensional seismic data as hard data and geostatistical parameters as trend constraints, through a stochastic simulation algorithm.

[0116] The reconstruction module is used to construct a three-dimensional seismic amplitude attribute model based on seismic attribute values, and to convert the three-dimensional seismic amplitude attribute model into a three-dimensional seismic data volume through simulation perturbation algorithm and seismic amplitude values;

[0117] The second modeling module is used to construct a fine-grained geological steering model of a horizontal well by using the three-dimensional seismic data volume as a physical constraint.

[0118] The guidance module is used to guide the drilling process geologically using a fine horizontal well geological guidance model.

[0119] The first modeling module includes:

[0120] The matching module is used to optimize the velocity field and adjust the seismic interpretation horizon by integrating well logging data and well logging data, so that the seismic interpretation horizon data matches the actual drilling results, with the ultimate goal of increasing the matching degree.

[0121] The first partitioning module is used to partition a horizontal modeling grid on a horizontal plane according to the set target well accuracy requirements;

[0122] The interpolation module is used to perform inter-well interpolation using seismic interpretation layer data to obtain finely modeled 3D structural surfaces;

[0123] The second partitioning module is used to partition the vertical modeling mesh on the longitudinal plane, establish multiple three-dimensional structural surfaces, and obtain a fine geological framework network model.

[0124] The guidance module includes:

[0125] The first judgment module is used to perform forward modeling of horizontal well curves during drilling and to determine whether the measurement-while-drilling wellbore is consistent with the fine horizontal well geological steering model.

[0126] The correction module is used to correct the fine horizontal well geological steering model when the first judgment module determines that the model does not match.

[0127] The second judgment module is used to determine whether the wellbore trajectory passes through the sweet spot required by the geological design when the first judgment module judges the composite, and whether the subsequent trajectory is parallel to the undulation of the formation structure.

[0128] The control module is used to adjust the drilling trajectory when the second judgment module determines that it is not true, and to control the drill bit to drill forward when the second judgment module determines that it is true.

[0129] In this embodiment, all control modules can be individual processing chips, multiple control areas within a processing chip, or control program modules within a single chip.

[0130] Example 5

[0131] A geological guidance terminal based on seismic data reconstruction includes a memory, a processor, and a computer program stored in the memory and executable on the processor. The processor, when executing the computer program, implements the steps of the geological guidance method based on seismic data reconstruction as described above.

[0132] Memory is used to store software programs and modules. The processor executes various terminal functions and data processing by running the software programs and modules stored in memory. Memory can mainly consist of a program storage area and a data storage area. The program storage area can store the operating system, at least one executable program required for a given function, etc.

[0133] The storage data area can store data created based on the use of the terminal. Furthermore, the memory can include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory, or other volatile solid-state storage devices.

[0134] A computer-readable storage medium storing a computer program, characterized in that, when executed by a processor, the computer program implements the steps of a geological guidance method based on seismic data reconstruction as described above.

[0135] Without loss of generality, computer-readable media can include computer storage media and communication media. Computer storage media include volatile and non-volatile, removable and non-removable media implemented using any method or technology for storing information such as computer-readable instruction data structures, program modules, or other data. Computer storage media include RAM, ROM, EPROM, EEPROM, flash memory or other solid-state storage technologies, CD-ROM, DVD or other optical storage, magnetic tape cassettes, magnetic tape, disk storage, or other magnetic storage devices. Of course, those skilled in the art will recognize that computer storage media are not limited to the above-mentioned types. The aforementioned system memories and mass storage devices can be collectively referred to as memory.

[0136] In the description of this specification, the references to terms such as "one embodiment / mode," "some embodiments / modes," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment / mode or example is included in at least one embodiment / mode or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment / mode or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments / modes or examples. Furthermore, without contradiction, those skilled in the art can combine and integrate the different embodiments / modes or examples described in this specification, as well as the features of different embodiments / modes or examples.

[0137] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0138] Those skilled in the art should understand that the above embodiments are merely for illustrating the present invention and are not intended to limit the scope of the invention. Those skilled in the art can make other changes or modifications based on the above invention, and these changes or modifications still fall within the scope of the present invention.

Claims

1. A geological guidance method based on seismic data reconstruction, characterized in that, include: Determine the region's two-dimensional seismic data, well logging data, well logging data, and seismic interpretation horizon data; Construct a refined geological framework network model; Two-dimensional seismic data are resampled in a fine geological framework network model to assign seismic attribute values ​​to the three-dimensional geological grid space; Based on the regional geological sedimentary patterns and by analyzing the statistical patterns of seismic attribute values ​​in various strata, geostatistical parameters were obtained. Using resampled two-dimensional seismic data as hard data and geostatistical parameters as trend constraints, the seismic amplitude values ​​in three-dimensional geological grid space are simulated through a stochastic simulation algorithm. A three-dimensional seismic amplitude attribute model is constructed based on seismic attribute values, and the three-dimensional seismic amplitude attribute model is transformed into a three-dimensional seismic data volume through simulation perturbation algorithm and seismic amplitude values; Using 3D seismic data as physical constraints, a refined geological steering model for horizontal wells is constructed. Geological guidance of the drilling process is achieved using a refined horizontal well geological steering model; The method for constructing a refined geological framework network model includes: By integrating well logging data and well logging data, optimizing the velocity field, and adjusting the seismic interpretation horizon, the seismic interpretation horizon data is matched with the actual drilling results, with the ultimate goal of increasing the matching degree. Set the target well accuracy requirements and divide the horizontal modeling grid on the horizontal plane; By performing well-to-well interpolation using seismic interpretation of stratigraphic data, a finely modeled three-dimensional structural surface is obtained; Vertical modeling meshes are divided on the longitudinal plane to establish multiple three-dimensional structural surfaces, thereby obtaining a fine geological framework network model.

2. The geological guidance method based on seismic data reconstruction according to claim 1, characterized in that, The statistical laws are obtained through probability distribution functions and variation functions; The distribution characteristics of earthquake amplitude values ​​in three-dimensional space are obtained by using probability distribution functions, and the three-dimensional normal distribution curve of earthquake amplitude values ​​is determined. By using the variogram function, the parameters of the variogram function are set according to the magnitude, frequency, and phase changes of the earthquake amplitude, and the spatial positional relationship and correlation between the earthquake amplitudes of unknown points and known points are obtained.

3. The geological guidance method based on seismic data reconstruction according to claim 2, characterized in that, The methods for using the probability distribution function include: The range of the normal distribution of earthquake amplitude values ​​was statistically analyzed, and the corresponding normal distribution characteristics were determined. Using the normal distribution characteristics as a trend constraint, a three-dimensional normal distribution curve of earthquake amplitude values ​​is simulated; The mathematical expression for the variation function is: In the formula, Indicates distance as The number of This represents the distance input when calculating spatial correlation. Let a random function, the difference function, be used. The first and second moments depend only on ; The range, sill value, and nugget value are determined using a variogram function, where the range is... When the steady-state value is reached Value, base value When the steady-state value is reached Value, the value of a nugget Non-zero time value.

4. The geological guidance method based on seismic data reconstruction according to claim 1, characterized in that, The random simulation algorithm is either a truncated Gaussian simulation algorithm or an indicator Kriging simulation algorithm.

5. The geological guidance method based on seismic data reconstruction according to claim 1, characterized in that, Methods for geological steering of the drilling process using refined horizontal well geological steering models include: Drill the well and perform forward modeling of the horizontal well profile. Determine whether the measurement-while-drilling (MWD) wellbore conforms to the refined horizontal well geological steering model. If they do not conform, modify the refined horizontal well geological steering model; if they conform, then: Determine whether the wellbore trajectory passes through the sweet spot required by the geological design, and whether the subsequent trajectory is parallel to the undulation of the formation. If not, adjust the drilling trajectory; if so, continue drilling.

6. A geological guidance device based on seismic data reconstruction, characterized in that, include: The determination module is used to determine the two-dimensional seismic data, well logging data, well logging data, and seismic interpretation horizon data of the region; The first modeling module is used to construct a fine geological framework network model; The assignment module is used to resample two-dimensional seismic data in a fine geological framework network model and assign seismic attribute values ​​to the three-dimensional geological grid space. The analysis module is used to obtain geostatistical parameters by analyzing the statistical regularities of seismic attribute values ​​of various strata based on regional geological sedimentary patterns. The simulation module is used to simulate the earthquake amplitude values ​​in a three-dimensional geological grid space using resampled two-dimensional seismic data as hard data and geostatistical parameters as trend constraints, through a stochastic simulation algorithm. The reconstruction module is used to construct a three-dimensional seismic amplitude attribute model based on seismic attribute values, and to convert the three-dimensional seismic amplitude attribute model into a three-dimensional seismic data volume through simulation perturbation algorithm and seismic amplitude values; The second modeling module is used to construct a fine-grained geological steering model of a horizontal well by using the three-dimensional seismic data volume as a physical constraint. The guidance module is used to guide the drilling process geologically using a fine horizontal well geological guidance model; The first modeling module includes: The matching module is used to optimize the velocity field and adjust the seismic interpretation horizon by integrating well logging data and well logging data, so that the seismic interpretation horizon data matches the actual drilling results, with the ultimate goal of increasing the matching degree. The first partitioning module is used to partition a horizontal modeling grid on a horizontal plane according to the set target well accuracy requirements; The interpolation module is used to perform inter-well interpolation using seismic interpretation layer data to obtain finely modeled 3D structural surfaces; The second partitioning module is used to partition the vertical modeling mesh on the longitudinal plane, establish multiple three-dimensional structural surfaces, and obtain a fine geological framework network model. The guidance module includes: The first judgment module is used to perform forward modeling of horizontal well curves during drilling and to determine whether the measurement-while-drilling wellbore is consistent with the fine horizontal well geological steering model. The correction module is used to correct the fine horizontal well geological steering model when the first judgment module determines that the model does not match. The second judgment module is used to determine whether the wellbore trajectory passes through the sweet spot required by the geological design when the first judgment module judges the composite, and whether the subsequent trajectory is parallel to the undulation of the formation structure. The control module is used to adjust the drilling trajectory when the second judgment module determines that it is not true, and to control the drill bit to drill forward when the second judgment module determines that it is true.

7. A geological guidance terminal based on seismic data reconstruction, 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 steps of a geological guidance method based on seismic data reconstruction as described in any one of claims 1-5.

8. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of a geological guidance method based on seismic data reconstruction as described in any one of claims 1-5.

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