Method and device for determining development parameters of a hydrocarbon reservoir

Abstract

This invention provides a method and apparatus for determining oil and gas reservoir development parameters, comprising: constructing an analogy sample library of oil and gas reservoir parameters covering geology, geophysics, and development parameters; acquiring geological and geophysical data of oil and gas reservoirs in the target area, and selecting analogy sample data with a matching degree reaching a preset threshold from the sample library; determining a comprehensive correction coefficient based on the difference between the geophysical data of the target area and the analogy samples, and calculating preliminary values ​​of development parameters for the target area by combining the coefficient with the analogy sample data; and optimizing the preliminary values ​​using a genetic algorithm based on preset constraints to obtain the development parameters of the oil and gas reservoirs in the target area. This invention determines the correction coefficient through multi-dimensional geological and geophysical analogy, calculates and optimizes parameters by combining sample development data, and achieves rapid and objective determination of development parameters for oil and gas reservoirs with low exploration levels. This improves the rationality and engineering adaptability of parameter design and provides reliable technical support for the preparation of oil and gas reservoir development plans.

Description

Technical Field

[0001] This invention belongs to the field of oil and gas exploration and development technology, and in particular relates to a method and apparatus for determining oil and gas reservoir development parameters by integrating geological-geophysical qualitative analogy, quantitative correction and dynamic iteration. Background Technology

[0002] In the field of oil and gas exploration and development, new overseas blocks and prospective traps with low exploration levels generally lack drilling data, and the determination of their oil and gas reservoir development parameters is highly dependent on the global analogy method.

[0003] Existing analogy techniques have significant shortcomings in practical applications. On the one hand, they are heavily reliant on quantitative seismic data (such as SEGY data), well logging, and development dynamics data. Acquiring such data is costly, time-consuming, and often difficult due to commercial confidentiality, creating a data bottleneck. On the other hand, the analogy process often focuses on matching static geological parameters, and parameter correction and determination rely heavily on expert experience, resulting in strong subjectivity and poor consistency. Furthermore, development parameters determined by existing methods are often out of sync with actual engineering constraints such as recovery rate and production capacity, making these parameters infeasible in engineering implementation and failing to meet the practical need for rapid and objective determination of oil and gas reservoir development parameters in low-exploration areas. Summary of the Invention

[0004] This invention provides a method for determining oil and gas reservoir development parameters. By determining correction coefficients through multi-dimensional geological and geophysical analogies, and combining sample development data with these correction coefficients to calculate development parameters, this method achieves rapid and objective determination of development parameters for oil and gas reservoirs with low exploration levels. This improves the rationality and engineering adaptability of parameter design and provides reliable technical support for oil and gas reservoir development schemes. The method for determining oil and gas reservoir development parameters includes: Construct an analogy sample library for oil and gas reservoir parameters; the analogy sample library includes analogy sample data; the analogy sample data includes geological data, geophysical data, and development parameters of historically developed oilfields; the geophysical data includes seismic facies type and amplitude data; Obtain geological and geophysical data of oil and gas reservoirs in the target area. Based on the geological and geophysical data of oil and gas reservoirs in the target area, select analogous sample data with a matching degree reaching a preset threshold from the oil and gas reservoir parameter analogy sample library, and use them as analogous sample data of oil and gas reservoirs in the target area. Based on the geophysical data of the target area's oil and gas reservoirs and the analog sample data of the target area's oil and gas reservoirs, a comprehensive correction coefficient is determined; the comprehensive correction coefficient includes seismic facies correction coefficient and amplitude correction coefficient. Based on the analog sample data of oil and gas reservoirs in the target area and the comprehensive correction coefficient, the preliminary values ​​of the development parameters of oil and gas reservoirs in the target area are calculated. Based on preset constraints, a genetic algorithm is used to optimize the preliminary values ​​of oil and gas reservoir development parameters in the target area to obtain the oil and gas reservoir development parameters in the target area; the preset constraints include recovery rate constraints and production capacity constraints.

[0005] This invention provides an oil and gas reservoir development parameter determination device. It determines correction coefficients through multi-dimensional geological and geophysical analogies, and calculates development parameters by combining sample development data with the correction coefficients. This achieves rapid and objective determination of development parameters for oil and gas reservoirs with low exploration levels, improving the rationality and engineering adaptability of parameter design, and providing reliable technical support for oil and gas reservoir development schemes. The oil and gas reservoir development parameter determination device includes: An analogy sample library construction module is used to construct an analogy sample library for oil and gas reservoir parameters. The analogy sample library includes analogy sample data, which includes geological data, geophysical data, and development parameters of historically developed oilfields. The geophysical data includes seismic facies types and amplitude data. The analog sample data filtering module is used to acquire geological and geophysical data of oil and gas reservoirs in the target area. Based on the geological and geophysical data of oil and gas reservoirs in the target area, it filters analog sample data with a matching degree reaching a preset threshold from the oil and gas reservoir parameter analog sample library and uses them as analog sample data of oil and gas reservoirs in the target area. The comprehensive correction coefficient determination module is used to determine the comprehensive correction coefficient based on the geophysical data of the target area's oil and gas reservoirs and the analog sample data of the target area's oil and gas reservoirs; the comprehensive correction coefficient includes the seismic facies correction coefficient and the amplitude correction coefficient; A module for calculating preliminary values ​​of development parameters has been developed to calculate preliminary values ​​of development parameters for oil and gas reservoirs in the target area based on analog sample data and comprehensive correction coefficients. The development parameter determination module is used to optimize the preliminary values ​​of oil and gas reservoir development parameters in the target area using a genetic algorithm based on preset constraints, so as to obtain the development parameters of the oil and gas reservoir in the target area; the preset constraints include recovery rate constraints and production capacity constraints.

[0006] This invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the above-described method for determining oil and gas reservoir development parameters.

[0007] This invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for determining oil and gas reservoir development parameters.

[0008] This invention also provides a computer program product, which includes a computer program that, when executed by a processor, implements the above-described method for determining oil and gas reservoir development parameters.

[0009] In this embodiment of the invention, an analogy sample library for oil and gas reservoir parameters is constructed. This library includes analogy sample data, which includes geological data, geophysical data, and development parameters of historically developed oilfields. The geophysical data includes seismic facies type and amplitude data. Geological and geophysical data of oil and gas reservoirs in the target area are acquired. Based on this data, analogy sample data with a matching degree reaching a preset threshold is selected from the analogy sample library and used as analogy sample data for the target area. A comprehensive correction coefficient is determined based on the geophysical data and the analogy sample data for the target area. The coefficients include seismic facies correction coefficients and amplitude correction coefficients; based on the target area's oil and gas reservoir analogy sample data and comprehensive correction coefficients, preliminary values ​​of the target area's oil and gas reservoir development parameters are calculated; based on preset constraints, a genetic algorithm is used to constrain and optimize the preliminary values ​​of the target area's oil and gas reservoir development parameters, thus obtaining the target area's oil and gas reservoir development parameters; the preset constraints include recovery rate constraints and production capacity constraints; this embodiment of the invention determines correction coefficients through multi-dimensional geological and geophysical analogies, and calculates development parameters by combining sample development data and correction coefficients, realizing the rapid and objective determination of development parameters for low-exploration-level oil and gas reservoirs, improving the rationality and engineering adaptability of parameter design, and providing reliable technical support for oil and gas reservoir development schemes. Attached Figure Description

[0010] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. In the drawings: Figure 1 This is a flowchart of the method for determining oil and gas reservoir development parameters in an embodiment of the present invention; Figure 2 This is a specific example diagram of screening analog sample data of oil and gas reservoirs in the target area in an embodiment of the present invention; Figure 3 This is a specific example diagram illustrating the determination of the comprehensive correction coefficient in an embodiment of the present invention; Figure 4 This is a specific example diagram illustrating the calculation of preliminary values ​​for development parameters in an embodiment of the present invention; Figure 5 This is a specific example diagram illustrating parameter calibration in an embodiment of the present invention; Figure 6 This is a specific example diagram illustrating the calculation of development parameters in an embodiment of the present invention; Figure 7 This is a structural example diagram of the oil and gas reservoir development parameter determination device in an embodiment of the present invention; Figure 8 This is a specific example diagram of the structure of the oil and gas reservoir development parameter determination device in an embodiment of the present invention; Figure 9 This is a specific example diagram of the structure of the oil and gas reservoir development parameter determination device in an embodiment of the present invention; Figure 10 This is a structural diagram of a computer device in an embodiment of the present invention. Detailed Implementation

[0011] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings. Here, the illustrative embodiments of the present invention and their descriptions are used to explain the present invention, but are not intended to limit the present invention.

[0012] As mentioned earlier, in the early stages of oil and gas exploration, when determining key development parameters for targets with low exploration levels, existing technologies mainly rely on the global analogy method. This method requires detailed quantitative seismic and well logging data from the global analogy area and focuses primarily on the analogy of static geological parameters. It lacks effective utilization of geophysical information, and the parameter determination process is highly dependent on expert experience. Furthermore, it does not incorporate optimization based on engineering economic constraints and lacks dynamic updating and iteration capabilities. When data in the target area is scarce, it suffers from problems such as data acquisition bottlenecks, low reliability of analogies, strong subjectivity in parameter determination, and poor engineering feasibility of the results.

[0013] To address this issue, the inventors discovered that by constructing an analog sample library encompassing geological, geophysical, and development data, a matching system for geological screening and geophysical verification can be established. Qualitative characteristics can be quantified into correction coefficients, and a geological engineering constraint coupling mechanism can be introduced. This allows for the rapid, objective, and feasible determination of key development parameters for oil and gas reservoirs in low-exploration target areas without relying on difficult-to-obtain quantitative data.

[0014] Figure 1 This is a flowchart of the method for determining oil and gas reservoir development parameters in an embodiment of the present invention, such as... Figure 1 As shown, the method for determining the development parameters of this oil and gas reservoir includes: Step 101: Construct an analogy sample library for oil and gas reservoir parameters; the analogy sample library includes analogy sample data; the analogy sample data includes geological data, geophysical data, and development parameters of historically developed oilfields; the geophysical data includes seismic facies type and amplitude data; Step 102: Obtain geological and geophysical data of oil and gas reservoirs in the target area. Based on the geological and geophysical data of oil and gas reservoirs in the target area, select analogous sample data with a matching degree reaching a preset threshold from the oil and gas reservoir parameter analogy sample library, and use them as analogous sample data of oil and gas reservoirs in the target area. Step 103: Determine the comprehensive correction coefficient based on the geophysical data of the target area's oil and gas reservoirs and the analog sample data of the target area's oil and gas reservoirs; the comprehensive correction coefficient includes the seismic facies correction coefficient and the amplitude correction coefficient; Step 104: Based on the analog sample data of oil and gas reservoirs in the target area and the comprehensive correction coefficient, calculate the preliminary values ​​of the development parameters of oil and gas reservoirs in the target area; Step 105: Based on preset constraints, a genetic algorithm is used to optimize the preliminary values ​​of oil and gas reservoir development parameters in the target area to obtain the oil and gas reservoir development parameters in the target area; the preset constraints include recovery rate constraints and production capacity constraints.

[0015] Depend on Figure 1 As shown in the flowchart, in this embodiment of the invention, an oil and gas reservoir parameter analogy sample library is constructed. This library includes analogy sample data, which includes geological data, geophysical data, and development parameters of historically developed oilfields. The geophysical data includes seismic facies type and amplitude data. Geological and geophysical data of the target area's oil and gas reservoirs are acquired. Based on this data, analogy sample data with a matching degree reaching a preset threshold is selected from the oil and gas reservoir parameter analogy sample library and used as the target area's oil and gas reservoir analogy sample data. A comprehensive correction coefficient is determined based on the target area's oil and gas reservoir geophysical data and the target area's oil and gas reservoir analogy sample data. This comprehensive correction coefficient includes seismic facies correction coefficients and amplitude correction coefficients. Preliminary values ​​of the target area's oil and gas reservoir development parameters are calculated based on the target area's oil and gas reservoir analogy sample data and the comprehensive correction coefficients. Based on preset constraints, a genetic algorithm is used to optimize the preliminary values ​​of the target area's oil and gas reservoir development parameters to obtain the target area's oil and gas reservoir development parameters. The preset constraints include recovery rate constraints and production capacity constraints.

[0016] Compared to existing technologies that rely on global analogy to determine key development parameters of oil and gas reservoirs, which depend on a large amount of quantitative measured data, focus only on analogy of static geological parameters, rely on expert experience for parameter determination, and do not incorporate optimization based on engineering and economic constraints, this new approach constructs an analogy sample library of oil and gas reservoir parameters that includes geological, geophysical, and development parameters. It combines geological and geophysical data of the target area to screen matching analogy sample data, determines a comprehensive correction coefficient including seismic facies and amplitude correction coefficients based on differences in geophysical data, calculates preliminary values ​​of development parameters, and then uses a genetic algorithm to optimize the final development parameters based on preset constraints such as recovery rate and production capacity. This approach enables the rapid and objective determination of key development parameters for oil and gas reservoirs in target areas with low exploration levels and no drilling data. It overcomes the bottleneck of quantitative data acquisition, improves the reliability of analogy matching and the accuracy of parameter determination, and simultaneously ensures the engineering feasibility and economic effectiveness of development parameters, providing reliable technical support for oil and gas exploration and development.

[0017] In step 101, an analogy sample library for oil and gas reservoir parameters is constructed. The analogy sample library for oil and gas reservoir parameters includes analogy sample data. The analogy sample data includes geological data, geophysical data, and development parameters of historically developed oilfields. The geophysical data includes seismic facies types and amplitude data.

[0018] In a specific embodiment, core data from no less than 100 developed oil and gas fields are collected as analog sample data. The analog sample data covers geological basic data, geophysical qualitative data (including), and development engineering parameters of developed oil fields worldwide.

[0019] The geological data includes basin type, sedimentary environment of main reservoirs, reservoir lithology, fluid properties, porosity, permeability, etc.; the geophysical qualitative data includes seismic facies type, amplitude intensity description, continuity qualitative description, etc.; and the development parameters include initial production of a single well, recovery rate, stable production period, construction period, development method, and surface facility capacity, etc.

[0020] All collected analog sample data undergoes outlier removal and normalization standardization processing. A dual-label system of geological core labels and geophysical qualitative labels is constructed for each sample to complete the construction of the oil and gas reservoir parameter analog sample library. A dynamic update mechanism is established for the sample library to achieve continuous supplementation and improvement of sample data. Specifically, the sample library has a semi-annual dynamic update mechanism.

[0021] Figure 2 This is a specific example diagram of screening target area oil and gas reservoir analog sample data in an embodiment of the present invention, as shown in the figure. Figure 2As shown, based on the geological and geophysical data of the target area's oil and gas reservoirs, analogous sample data with a matching degree reaching a preset threshold are selected from the oil and gas reservoir parameter analogy sample library and used as the target area's oil and gas reservoir analogy sample data. This may include: Step 201: Based on the geological data of the target area's oil and gas reservoirs, the geological data of the analog sample data in the oil and gas reservoir parameter analog sample library is screened according to a preset priority to obtain the analog sample data whose geological data matching degree reaches the preset geological matching threshold; the priority is arranged from largest to smallest as basin type, reservoir sedimentary environment, reservoir lithology, and fluid properties. Step 202: Based on the geophysical data of the target area's oil and gas reservoirs, the analog sample data whose geological data matching degree reaches the preset geological matching threshold are screened for seismic facies type and amplitude. The sample data whose matching degree reaches the preset threshold after screening are used as the analog sample data of the target area's oil and gas reservoirs. The amplitude screening includes amplitude intensity screening and amplitude continuity screening.

[0022] In a specific embodiment, based on the geological and geophysical data of the target area's oil and gas reservoirs, analogous sample data with a matching degree reaching a preset threshold are selected from the oil and gas reservoir parameter analogy sample library as the target area's oil and gas reservoir analogy sample data, including: Geological data is filtered according to preset priorities: Based on the geological data of oil and gas reservoirs in the target area, a three-level geological homology screening was conducted in the oil and gas reservoir parameter analogy sample library according to the preset priority from high to low: basin type → reservoir sedimentary environment → reservoir lithology → fluid properties. The analogy sample data were matched precisely at each level in turn, and samples with mismatched geological data were eliminated. Finally, analogy sample data with a geological data matching degree reaching the preset threshold were obtained. Among them, the first-level screening (same basin type) retained ≥20 samples, the second-level screening (same sedimentary environment) retained ≥12 samples, and the third-level screening (same lithology-fluid) retained ≥8 samples.

[0023] A dual screening of geophysical data was conducted to determine the final analog sample data: Based on the geophysical data of the target area's oil and gas reservoirs, a two-level geophysical qualitative screening is carried out on the analog sample data after geological data screening. First, a primary screening of seismic facies types is conducted, and samples that match the seismic facies types of the target area are retained. Then, a secondary screening of amplitude, which includes amplitude intensity screening and amplitude continuity screening, is conducted on the retained samples. The analog sample data that, after the two-level geophysical screening, reaches the preset threshold and has a number of no less than 5, are used as the analog sample data of the target area's oil and gas reservoirs.

[0024] Figure 3 This is a specific example diagram illustrating the determination of the comprehensive correction coefficient in an embodiment of the present invention, such as... Figure 3As shown, based on the geophysical data of the target area's oil and gas reservoirs and the analogous sample data of the target area's oil and gas reservoirs, a comprehensive correction coefficient is determined, which may include: Step 301: Obtain seismic facies type and amplitude data from the geophysical data of the target area's oil and gas reservoirs, as well as seismic facies type and amplitude data from the analog sample data; Step 302: Compare the seismic facies type and amplitude data of the target area oil and gas reservoirs with the analog sample data using the quantitative comparison method, and determine the seismic facies correction coefficient and amplitude correction coefficient based on the comparison results. Step 303: Calculate the comprehensive correction coefficient based on the seismic phase correction coefficient and the amplitude correction coefficient.

[0025] In a specific embodiment, a comprehensive correction coefficient is determined based on geophysical data of the target area's oil and gas reservoirs and analogous sample data of the target area's oil and gas reservoirs, including: Obtain the corresponding geophysical data: The seismic facies type, amplitude intensity, and amplitude continuity data of the target area's oil and gas reservoir geophysical data are obtained. At the same time, the corresponding seismic facies type, amplitude intensity, and amplitude continuity data of the target area's oil and gas reservoir analog sample data are retrieved simultaneously to provide a data basis for subsequent difference comparison.

[0026] Quantitative comparison of differences to determine individual correction coefficients: A quantitative comparative analysis was conducted on the seismic facies types and amplitude data of the target area's oil and gas reservoirs and analog sample data. Based on the comparison results, seismic facies correction coefficients were determined, such as the continuity correction coefficient K1 and the amplitude correction coefficient, such as the amplitude strength correction coefficient K2. Specifically, K1 was set to 1.10-1.2 when the target area had better continuity, 1.00 when it was consistent with the analog sample, and 0.80-0.90 when the continuity was poor. K2 was set to 1.05-1.1 when the target area had stronger amplitude, 1.00 when it was consistent with the analog sample, and 0.85-0.95 when the amplitude was weaker.

[0027] Calculate the overall correction factor: The determined seismic phase correction coefficient (K1) and amplitude correction coefficient (K2) are multiplied to obtain the comprehensive correction coefficient K, i.e., K = K1 × K2. The effective range of the comprehensive correction coefficient K is 0.70-1.25.

[0028] Figure 4 This is a specific example diagram illustrating the calculation of preliminary values ​​for development parameters in an embodiment of the present invention, as shown below. Figure 4 As shown, based on analogous sample data of oil and gas reservoirs in the target area and comprehensive correction coefficients, the preliminary values ​​of development parameters for oil and gas reservoirs in the target area can be calculated, including: Step 401: Statistically analyze the development data in the target area oil and gas reservoir analog sample data to obtain the statistical values ​​of the development data in the target area oil and gas reservoir analog sample data; the statistical values ​​include the mean and standard deviation; Step 402: Calculate the preliminary values ​​of the development parameters of the oil and gas reservoirs in the target area based on the statistical values ​​and comprehensive correction coefficients of the development data in the analog sample data of the target area oil and gas reservoirs.

[0029] In a specific embodiment, based on the target area's oil and gas reservoir analogy sample data and comprehensive correction coefficients, preliminary values ​​of the target area's oil and gas reservoir development parameters are calculated, including: Statistical analogy sample development data feature values: Statistical analysis is performed on the development engineering data in the analog sample data of oil and gas reservoirs in the target area to calculate the statistical values ​​corresponding to key development parameters such as initial production and recovery rate of single wells. The statistical values ​​specifically include the average value and standard deviation of each development parameter, forming the statistical characteristic results of the development parameters of the analog sample.

[0030] Preliminary parameter values ​​were calculated based on the comprehensive correction factors: The average value of the key development parameters of the analog sample obtained in step 401 is multiplied by the comprehensive correction coefficient to calculate the preliminary values ​​of each key development parameter of the target area's oil and gas reservoir. For example: Preliminary initial production value of a single well = Average initial production value of a single well × Comprehensive correction coefficient; Preliminary recovery rate value = Average recovery rate × Comprehensive correction coefficient.

[0031] Figure 5 This is a specific example diagram of parameter calibration in an embodiment of the present invention, as shown below. Figure 5 As shown, after calculating the preliminary values ​​of the development parameters for oil and gas reservoirs in the target area based on analogous sample data and comprehensive correction coefficients, the following can be included: Step 501: Obtain reservoir parameters of oil and gas reservoirs in the target area through geological inversion; the reservoir parameters include porosity, permeability, and thickness; Step 502: Determine the calibration coefficients based on the reservoir parameters of the target area's oil and gas reservoirs using a preset numerical model; the preset numerical model is a linear or nonlinear numerical model constructed based on the reservoir parameters of the target area's oil and gas reservoirs. Step 503: Use calibration coefficients to calibrate the preliminary values ​​of oil and gas reservoir development parameters in the target area to obtain the calibrated preliminary values ​​of oil and gas reservoir development parameters in the target area.

[0032] In a specific embodiment, after calculating the preliminary values ​​of the development parameters for the target area's oil and gas reservoirs, the preliminary values ​​of the development parameters are calibrated, including: Quantitative reservoir parameters of oil and gas reservoirs in the target area are obtained by means of seismic inversion or regional geological data analysis. The reservoir parameters include at least one of porosity, permeability, and thickness. At the same time, the mean values ​​of the corresponding reservoir parameters in the analog sample data of oil and gas reservoirs in the target area are retrieved.

[0033] Based on the type and quantity of reservoir parameters acquired in the target area, corresponding linear or nonlinear preset numerical models are constructed. The ratio of the target area reservoir parameters to the mean values ​​of analog sample reservoir parameters, along with the comprehensive correction coefficient, are substituted into the model. The calibration coefficient Γ is then calculated using preset weighting coefficients. Single-parameter models, such as porosity models, are also included. Γ=α×(Φ_target / Φ_mean)+ β×K Penetration model: Γ=α×(K_target / K_mean)+ β×K Thickness model: Γ=α×(H_target / H_mean)+ β×K Multi-parameter integrated model: Γ=α×(Φ_target / Φ_mean)+ α×(K_target / K_mean)+ α×(H_target / H_mean)+ β×K Wherein, Φ_target is the porosity of the target region, Φ_mean is the mean porosity of the analog sample, K_target is the permeability of the target region, K_mean is the mean permeability of the analog sample, H_target is the thickness of the target region, H_mean is the mean thickness of the analog sample, and α and β are preset weighting coefficients.

[0034] The calculated calibration coefficient Γ is multiplied with the preliminary values ​​of the target area's oil and gas reservoir development parameters. The calibration coefficient is then used to accurately calibrate the preliminary values, resulting in the calibrated preliminary values ​​of the target area's oil and gas reservoir development parameters, thus achieving further optimization of the development parameters.

[0035] Figure 6 This is a specific example diagram illustrating the calculation of development parameters in an embodiment of the present invention, such as... Figure 6 As shown, a genetic algorithm is used to perform constrained optimization on the preliminary values ​​of oil and gas reservoir development parameters in the target area, resulting in the oil and gas reservoir development parameters for the target area, which may include: Step 601: Substitute the preliminary values ​​of the target area oil and gas reservoir development parameters into the optimization model of the genetic algorithm, and use the preset constraints as the algorithm's solution limit; Step 602: Use a genetic algorithm to find the optimal solution for oil and gas reservoir development parameters that meet the preset constraints, and use it as the development parameters for oil and gas reservoirs in the target area.

[0036] In a specific embodiment, a genetic algorithm is used to perform constraint optimization on the preliminary values ​​of oil and gas reservoir development parameters in the target area to obtain the oil and gas reservoir development parameters in the target area, including: Construct a genetic algorithm optimization solution model: The calibrated preliminary values ​​of the target area's oil and gas reservoir development parameters are substituted into the optimization model of the genetic algorithm. The optimization variables are defined as core development parameters such as initial production of a single well, number of deployed wells, duration of stable production period, recovery rate, and production construction cycle. At the same time, preset constraints are used as the solution restrictions for the algorithm. The preset constraints include geological rationality constraints and engineering economic constraints. The geological constraints include a recovery rate in the range of 20%-40%, etc., and the engineering economic constraints include total production capacity ≤ FPSO processing capacity, investment payback period ≤ 10 years, and net present value (NPV) ≥ 0, etc.

[0037] Genetic algorithms use global optimization to obtain the optimal solution: With the dual optimization objectives of maximizing the utilization rate of engineering facilities and optimizing economic benefits, a genetic algorithm is used to perform multi-parameter global optimization on the optimization model. The combination of development parameters that simultaneously satisfies all preset constraints is selected, and the optimal solution is used as the final development parameters for the oil and gas reservoir in the target area. The output parameters include specific values ​​such as initial production of a single well, number of deployed wells, stable production period, recovery rate, and production construction cycle, ensuring that the parameters are both geologically reasonable and engineering economically feasible.

[0038] In this embodiment, after optimizing the preliminary values ​​of oil and gas reservoir development parameters in the target area using a genetic algorithm based on preset constraints to obtain the oil and gas reservoir development parameters in the target area, the method may further include: The development parameters of oil and gas reservoirs in the target area are added to the oil and gas reservoir parameter analogy sample library to obtain the updated oil and gas reservoir parameter analogy sample library.

[0039] In a specific embodiment, after obtaining the development parameters of the target area's oil and gas reservoirs, these parameters are added to the oil and gas reservoir parameter analogy sample library and the sample library is updated, including: The oil and gas reservoir development parameters of the target area identified in this study were integrated and sorted together with the corresponding geological and geophysical qualitative data. Data processing was completed according to the standardized specifications of the oil and gas reservoir parameter analogy sample library, and corresponding geological and geophysical dual labels were constructed for this set of data. The integrated and processed complete set of data of the target area was used as new analogy sample data and entered into the original oil and gas reservoir parameter analogy sample library to complete the content supplementation of the sample library and obtain an updated oil and gas reservoir parameter analogy sample library. This enables the sample library to be dynamically updated and provides richer analogy sample support for the determination of key oil and gas reservoir parameters in other target areas in the future.

[0040] The method for determining oil and gas reservoir development parameters according to the embodiments of the present invention has been verified to have the following beneficial effects: 1. Matching and verification are completed using geophysical data, eliminating the need to rely on quantitative SEGY seismic data from the global analog area, which is difficult to obtain, thus solving the core data pain point of evaluating blocks with low exploration levels.

[0041] 2. Improve the objectivity and accuracy of analogy matching. Through a matching system with three levels of geological screening and two levels of geophysical verification, qualitative differences are quantified into correction coefficients, significantly reducing subjective arbitrariness and reducing parameter prediction errors.

[0042] 3. Introduce dual-constraint optimization in geological engineering to ensure that the determined development parameters not only conform to underground geological laws, but also meet the implementation conditions and economic requirements of surface engineering, thereby improving the operability and decision support value of the parameters.

[0043] 4. Effectively solves the problems of difficulty in determining key parameters of oil and gas reservoirs, low reliability, and disconnect from engineering in scenarios with tight time and limited data, such as rapid screening and bidding evaluation of new overseas blocks, and provides oil and gas companies with an efficient and reliable technical evaluation tool for expanding new overseas projects.

[0044] This invention also provides an apparatus for determining oil and gas reservoir development parameters, as described in the following embodiments. Since the principle by which this apparatus solves the problem is similar to the method for determining oil and gas reservoir development parameters, the implementation of this apparatus can refer to the implementation of the method for determining oil and gas reservoir development parameters; repeated details will not be elaborated further.

[0045] Figure 7 This is a structural example diagram of the oil and gas reservoir development parameter determination device in an embodiment of the present invention, as shown below. Figure 7 As shown, the device for determining the development parameters of the oil and gas reservoir includes: The analogy sample library construction module 701 is used to construct an analogy sample library for oil and gas reservoir parameters. The analogy sample library for oil and gas reservoir parameters includes analogy sample data. The analogy sample data includes geological data, geophysical data, and development parameters of historically developed oilfields. The geophysical data includes seismic facies type and amplitude data. The analog sample data filtering module 702 is used to acquire geological and geophysical data of oil and gas reservoirs in the target area. Based on the geological and geophysical data of oil and gas reservoirs in the target area, it filters analog sample data with a matching degree reaching a preset threshold from the oil and gas reservoir parameter analog sample library and uses them as analog sample data of oil and gas reservoirs in the target area. The comprehensive correction coefficient determination module 703 is used to determine the comprehensive correction coefficient based on the geophysical data of the target area oil and gas reservoirs and the analog sample data of the target area oil and gas reservoirs; the comprehensive correction coefficient includes the seismic facies correction coefficient and the amplitude correction coefficient; The development parameter preliminary value calculation module 704 is used to calculate the preliminary values ​​of the development parameters of the oil and gas reservoirs in the target area based on the target area oil and gas reservoir analog sample data and the comprehensive correction coefficient. The development parameter determination module 705 is used to optimize the preliminary values ​​of the development parameters of the target area oil and gas reservoir based on preset constraints using a genetic algorithm, so as to obtain the development parameters of the target area oil and gas reservoir; the preset constraints include recovery rate constraints and production capacity constraints.

[0046] In one embodiment, the analog sample data filtering module 702 is specifically used for: Based on the geological data of oil and gas reservoirs in the target area, the geological data of the analog sample data in the oil and gas reservoir parameter analog sample library is screened according to the preset priority to obtain the analog sample data whose geological data matching degree reaches the preset geological matching threshold; the priority is arranged from largest to smallest as basin type, reservoir sedimentary environment, reservoir lithology, and fluid properties. Based on the geophysical data of the target area's oil and gas reservoirs, the analog sample data whose geological data matching degree reaches the preset geological matching threshold are screened for seismic facies type and amplitude. The sample data whose matching degree reaches the preset threshold after screening are used as the analog sample data of the target area's oil and gas reservoirs. The amplitude screening includes amplitude intensity screening and amplitude continuity screening.

[0047] In one embodiment, the comprehensive correction coefficient determination module 703 is specifically used for: Obtain seismic facies type and amplitude data from geophysical data of oil and gas reservoirs in the target area, as well as seismic facies type and amplitude data from analog sample data; For oil and gas reservoirs in the target area and analog sample data, the differences in seismic facies type and amplitude data are compared using a quantitative comparison method. Based on the comparison results, the seismic facies correction coefficient and amplitude correction coefficient are determined. The comprehensive correction factor is calculated based on the seismic phase correction factor and the amplitude correction factor.

[0048] In one embodiment, the preliminary value calculation module 704 for the development parameters is specifically used for: Statistical analysis is performed on the development data in the analog sample data of oil and gas reservoirs in the target area to obtain statistical values ​​of the development data in the analog sample data of oil and gas reservoirs in the target area; the statistical values ​​include the mean and standard deviation. Based on the statistical values ​​and comprehensive correction coefficients of the development data in the analog sample data of oil and gas reservoirs in the target area, the preliminary values ​​of the development parameters of oil and gas reservoirs in the target area are calculated.

[0049] Figure 8 This is a specific example diagram of the structure of the oil and gas reservoir development parameter determination device in an embodiment of the present invention, as shown below. Figure 8 As shown in one embodiment, Figure 7 The oil and gas reservoir development parameter determination device shown in the embodiment of the present invention may further include: a calibration module 801.

[0050] In one embodiment, the calibration module 801 is specifically used for: Reservoir parameters of oil and gas reservoirs in the target area are obtained through geological inversion; the reservoir parameters include porosity, permeability, and thickness. Based on the reservoir parameters of the oil and gas reservoirs in the target area, calibration coefficients are determined through a preset numerical model; the preset numerical model is a linear numerical model or a nonlinear numerical model constructed based on the reservoir parameters of the oil and gas reservoirs in the target area. The preliminary values ​​of oil and gas reservoir development parameters in the target area are calibrated using calibration coefficients to obtain the calibrated preliminary values ​​of oil and gas reservoir development parameters in the target area.

[0051] In one embodiment, the development parameter determination module 705 is specifically used for: The preliminary values ​​of the oil and gas reservoir development parameters in the target area are substituted into the optimization model of the genetic algorithm, and the preset constraints are used as the algorithm's solution limits. The optimal solution for oil and gas reservoir development parameters that meets the preset constraints is obtained by using a genetic algorithm, and this solution is used as the development parameters for oil and gas reservoirs in the target area.

[0052] Figure 9 This is a specific example diagram of the structure of the oil and gas reservoir development parameter determination device in an embodiment of the present invention, as shown below. Figure 9 As shown in one embodiment, Figure 7 The oil and gas reservoir development parameter determination device shown in the embodiment of the present invention may further include: an update module 901.

[0053] In one embodiment, the update module 901 is specifically used for: The development parameters of oil and gas reservoirs in the target area are added to the oil and gas reservoir parameter analogy sample library to obtain the updated oil and gas reservoir parameter analogy sample library.

[0054] Based on the aforementioned inventive concept, such as Figure 10 As shown, the present invention also proposes a computer device 1000, including a memory 1010, a processor 1020, and a computer program 1030 stored in the memory 1010 and executable on the processor 1020. When the processor 1020 executes the computer program 1030, it implements the aforementioned method for determining oil and gas reservoir development parameters.

[0055] This invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for determining oil and gas reservoir development parameters.

[0056] This invention also provides a computer program product, which includes a computer program that, when executed by a processor, implements the above-described method for determining oil and gas reservoir development parameters.

[0057] In this embodiment of the invention, an analogy sample library for oil and gas reservoir parameters is constructed. This library includes analogy sample data, which includes geological data, geophysical data, and development parameters of historically developed oilfields. The geophysical data includes seismic facies type and amplitude data. Geological and geophysical data of oil and gas reservoirs in the target area are acquired. Based on this data, analogy sample data with a matching degree reaching a preset threshold is selected from the analogy sample library and used as analogy sample data for the target area. A comprehensive correction coefficient is determined based on the geophysical data and the analogy sample data for the target area. The coefficients include seismic facies correction coefficients and amplitude correction coefficients; based on the target area's oil and gas reservoir analogy sample data and comprehensive correction coefficients, preliminary values ​​of the target area's oil and gas reservoir development parameters are calculated; based on preset constraints, a genetic algorithm is used to constrain and optimize the preliminary values ​​of the target area's oil and gas reservoir development parameters, thus obtaining the target area's oil and gas reservoir development parameters; the preset constraints include recovery rate constraints and production capacity constraints; this embodiment of the invention determines correction coefficients through multi-dimensional geological and geophysical analogies, and calculates development parameters by combining sample development data and correction coefficients, realizing the rapid and objective determination of development parameters for low-exploration-level oil and gas reservoirs, improving the rationality and engineering adaptability of parameter design, and providing reliable technical support for oil and gas reservoir development schemes.

[0058] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0059] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0060] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0061] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0062] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for determining oil and gas reservoir development parameters, characterized in that, include: Construct an analogy sample library for oil and gas reservoir parameters; the analogy sample library includes analogy sample data; the analogy sample data includes geological data, geophysical data, and development parameters of historically developed oilfields; the geophysical data includes seismic facies type and amplitude data; Obtain geological and geophysical data of oil and gas reservoirs in the target area. Based on the geological and geophysical data of oil and gas reservoirs in the target area, select analogous sample data with a matching degree reaching a preset threshold from the oil and gas reservoir parameter analogy sample library, and use them as analogous sample data of oil and gas reservoirs in the target area. Based on the geophysical data of the target area's oil and gas reservoirs and the analog sample data of the target area's oil and gas reservoirs, a comprehensive correction coefficient is determined; the comprehensive correction coefficient includes seismic facies correction coefficient and amplitude correction coefficient. Based on the analog sample data of oil and gas reservoirs in the target area and the comprehensive correction coefficient, the preliminary values ​​of the development parameters of oil and gas reservoirs in the target area are calculated. Based on preset constraints, a genetic algorithm is used to optimize the preliminary values ​​of oil and gas reservoir development parameters in the target area to obtain the oil and gas reservoir development parameters in the target area; the preset constraints include recovery rate constraints and production capacity constraints.

2. The method as described in claim 1, characterized in that, Based on the geological and geophysical data of the target area's oil and gas reservoirs, analogous sample data with a matching degree reaching a preset threshold are selected from the oil and gas reservoir parameter analogy sample library and used as the target area's oil and gas reservoir analogy sample data, including: Based on the geological data of oil and gas reservoirs in the target area, the geological data of the analog sample data in the oil and gas reservoir parameter analog sample library is screened according to the preset priority to obtain the analog sample data whose geological data matching degree reaches the preset geological matching threshold; the priority is arranged from largest to smallest as basin type, reservoir sedimentary environment, reservoir lithology, and fluid properties. Based on the geophysical data of the target area's oil and gas reservoirs, the analog sample data whose geological data matching degree reaches the preset geological matching threshold are screened for seismic facies type and amplitude. The sample data whose matching degree reaches the preset threshold after screening are used as the analog sample data of the target area's oil and gas reservoirs. The amplitude screening includes amplitude intensity screening and amplitude continuity screening.

3. The method as described in claim 1, characterized in that, Based on the geophysical data of the target area's oil and gas reservoirs and the analogous sample data of the target area's oil and gas reservoirs, a comprehensive correction coefficient is determined, including: Obtain seismic facies type and amplitude data from geophysical data of oil and gas reservoirs in the target area, as well as seismic facies type and amplitude data from analog sample data; For oil and gas reservoirs in the target area and analog sample data, the differences in seismic facies type and amplitude data are compared using a quantitative comparison method. Based on the comparison results, the seismic facies correction coefficient and amplitude correction coefficient are determined. The comprehensive correction factor is calculated based on the seismic phase correction factor and the amplitude correction factor.

4. The method as described in claim 1, characterized in that, Based on analogous sample data of oil and gas reservoirs in the target area and comprehensive correction coefficients, preliminary values ​​of development parameters for oil and gas reservoirs in the target area are calculated, including: Statistical analysis is performed on the development data in the analog sample data of oil and gas reservoirs in the target area to obtain statistical values ​​of the development data in the analog sample data of oil and gas reservoirs in the target area; the statistical values ​​include the mean and standard deviation. Based on the statistical values ​​and comprehensive correction coefficients of the development data in the analog sample data of oil and gas reservoirs in the target area, the preliminary values ​​of the development parameters of oil and gas reservoirs in the target area are calculated.

5. The method as described in claim 1, characterized in that, After calculating the preliminary values ​​of the development parameters for the target area's oil and gas reservoirs based on analogous sample data and comprehensive correction coefficients, the following are included: Reservoir parameters of oil and gas reservoirs in the target area are obtained through geological inversion; the reservoir parameters include porosity, permeability, and thickness. Based on the reservoir parameters of the oil and gas reservoirs in the target area, calibration coefficients are determined through a preset numerical model; the preset numerical model is a linear numerical model or a nonlinear numerical model constructed based on the reservoir parameters of the oil and gas reservoirs in the target area. The preliminary values ​​of oil and gas reservoir development parameters in the target area are calibrated using calibration coefficients to obtain the calibrated preliminary values ​​of oil and gas reservoir development parameters in the target area.

6. The method as described in claim 1, characterized in that, Based on preset constraints, a genetic algorithm is used to optimize the preliminary values ​​of oil and gas reservoir development parameters in the target area, resulting in the following development parameters: The preliminary values ​​of the oil and gas reservoir development parameters in the target area are substituted into the optimization model of the genetic algorithm, and the preset constraints are used as the algorithm's solution limits. The optimal solution for oil and gas reservoir development parameters that meets the preset constraints is obtained by using a genetic algorithm, and this solution is used as the development parameters for oil and gas reservoirs in the target area.

7. The method as described in claim 1, characterized in that, After obtaining the development parameters of the target area's oil and gas reservoirs by using a genetic algorithm to optimize the preliminary values ​​of the development parameters based on preset constraints, the process also includes: The development parameters of oil and gas reservoirs in the target area are added to the oil and gas reservoir parameter analogy sample library to obtain the updated oil and gas reservoir parameter analogy sample library.

8. A device for determining oil and gas reservoir development parameters, characterized in that, include: An analogy sample library construction module is used to construct an analogy sample library for oil and gas reservoir parameters. The analogy sample library includes analogy sample data, which includes geological data, geophysical data, and development parameters of historically developed oilfields. The geophysical data includes seismic facies types and amplitude data. The analog sample data filtering module is used to acquire geological and geophysical data of oil and gas reservoirs in the target area. Based on the geological and geophysical data of oil and gas reservoirs in the target area, it filters analog sample data with a matching degree reaching a preset threshold from the oil and gas reservoir parameter analog sample library and uses them as analog sample data of oil and gas reservoirs in the target area. The comprehensive correction coefficient determination module is used to determine the comprehensive correction coefficient based on the geophysical data of the target area's oil and gas reservoirs and the analog sample data of the target area's oil and gas reservoirs; the comprehensive correction coefficient includes the seismic facies correction coefficient and the amplitude correction coefficient; A module for calculating preliminary values ​​of development parameters has been developed to calculate preliminary values ​​of development parameters for oil and gas reservoirs in the target area based on analog sample data and comprehensive correction coefficients. The development parameter determination module is used to optimize the preliminary values ​​of oil and gas reservoir development parameters in the target area using a genetic algorithm based on preset constraints, so as to obtain the development parameters of the oil and gas reservoir in the target area; the preset constraints include recovery rate constraints and production capacity constraints.

9. 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 according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method of any one of claims 1-7.

11. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the method of any one of claims 1-7.

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