Reservoir reserve prediction method and device and storage medium
By acquiring and integrating the geological parameters of oil and gas fields and generating corresponding models, the problem of insufficient objectivity and accuracy in reservoir oil and gas reserve prediction is solved, and more accurate reserve prediction is achieved.
Patent Information
- Application Number
- CN202311159668.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2023-09-08
- Publication Date
- 2025-03-11
AI Technical Summary
The prior art has problems of insufficient objectivity and accuracy in reservoir oil and gas reserve prediction, especially in areas with few or no wells, which are difficult to accurately evaluate.
By obtaining the geological parameters of the target oil and gas field, including core data, logging data and seismic data, tectonic models, phase models and attribute models are generated, and the oil and gas system and oil and gas water interface are integrated to construct a reserve model to predict oil and gas reserves.
The objective and accurate prediction of reservoir oil and gas reserves was achieved, and the problems of insufficient geological theoretical basis and no actual data between wells in the existing technology were overcome, which improved the practicality and accuracy of the model.
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Abstract
Description
Technical Field
[0001] The embodiments of this specification relate to the field of geological exploration and development technology, and in particular to a reservoir reserve prediction method, device and storage medium. Background Art
[0002] With the improvement of computer performance, 3D geological modeling technology has made great progress since the late 1990s. Seismic data is rich and can reflect underground structure and sand body changes in a wide range in the horizontal direction. Making full use of seismic data can improve the accuracy of the model, which is valuable for predicting the formation, lithofacies and reservoir characteristics between drilling and control areas. Well logging data, that is, hard data, has a high resolution in the vertical direction and can provide local data. However, it is difficult to make accurate evaluations in areas with no wells or a small number of wells.
[0003] The existing technologies have their own adaptability and limitations in both deterministic modeling and stochastic modeling. Although multi-point geostatistics can objectively reflect the depositional laws of phases by using multiple phase sequence similarities and considering weights, it does not refer to inter-well seismic information, and the simulation results lack factual basis. The direct and indirect algorithms using seismic data have low credibility, and the calculated results are quite different from the actual ones. Therefore, there is an urgent need for a method that can objectively and accurately predict the oil and gas reserves of reservoirs. Summary of the invention
[0004] The purpose of the embodiments of this specification is to provide a reservoir reserve prediction method, device and storage medium to solve the problem of how to objectively and accurately predict the oil and gas reserves of a reservoir.
[0005] In order to solve the above technical problems, an embodiment of the present specification proposes a reservoir reserve prediction method, comprising: obtaining geological parameters of a target oil and gas field; the geological parameters include core data, logging data and seismic data; generating a structural model according to the geological parameters; the structural model is formed by matching a layer model and a fault model; the structural model is used to determine stratigraphic relationships and fault relationships; obtaining a phase model through phase simulation based on logging data; the phase model is used to indicate the distribution of sand bodies; constructing an attribute model based on the phase simulation results corresponding to the logging data and the phase model; determining the oil and gas system and the oil-gas-water interface through comprehensive reservoir geological analysis; the oil and gas system and the oil-gas-water interface are used to determine the reserve limit and reserve level; constructing a reserve model in combination with the structural model, phase model, attribute model, oil and gas system and the oil-gas-water interface; the reserve model is used to predict the oil and gas reserves of the target oil and gas field.
[0006] In some embodiments, the core data includes at least one of core description, physical property analysis and diagenesis analysis; the logging data includes at least one of logging LAS series data, logging interpretation data and test data; the seismic data includes at least one of three-dimensional data volume, seismic interpretation data and time-depth relationship.
[0007] In some embodiments, generating a structural model according to the geological parameters includes: obtaining a time domain grid and a longitudinal combination of plane polygons based on seismic interpretation data; converting the time domain into a depth domain to obtain a layer model in combination with the correspondence between the time domain and the depth; the layer model includes a layer grid; converting the longitudinal combination of plane polygons into a fault plane; the fault plane has a corresponding truncation relationship; matching the layer grid and the truncation relationship to obtain a fault model; matching the layer model and the fault model to form the structural model.
[0008] In some embodiments, the phase model is obtained through phase simulation based on well logging data, including: coarsening the well logging data into hard data; the hard data includes sedimentary phase data, well logging interpretation data, porosity, oil and gas saturation and oil and gas layer sand-to-situ ratio; using a random function to perform phase simulation on the hard data and seismic data to obtain a phase model; the random function includes at least one of a variogram, a vertical scale and a lateral probability setting.
[0009] In some embodiments, the attribute model is constructed based on the phase simulation results corresponding to the logging data and the phase model, including: coarsening the logging data into hard data; the hard data includes sedimentary phase data, logging interpretation data, porosity, oil and gas saturation and oil and gas layer sand-to-formation ratio; seismic data is obtained as soft data based on the attributes of the seismic data volume layer; geological relationships are determined based on the hard data and soft data; the geological relationships include sedimentary phase-physical properties, oil and gas properties, oil and gas layer sand-to-formation ratio-seismic attribute relationships; an attribute model is constructed based on the geological relationships; the attribute model includes porosity, oil and gas saturation and oil and gas layer sand-to-formation ratio models that conform to the base level cycle changes.
[0010] Based on the above implementation mode, the attribute model is constructed based on the geological relationship, including: using the ordered Gaussian algorithm, seismic attributes and sedimentary phase constraints to simulate the three-dimensional geological distribution of physical properties, oil and gas content and oil and gas layer sand-to-land ratio; constructing an attribute model according to the three-dimensional geological distribution of physical properties, oil and gas content and oil and gas layer sand-to-land ratio.
[0011] In some embodiments, the construction of a reserve model in combination with the structural model, phase model, property model, oil and gas system and oil-gas-water interface includes: establishing an oil-gas-water interface model, an effective reservoir volume model, a pore volume model and an oil and gas volume model based on the phase model, property model, oil and gas system and oil-gas-water interface respectively; and generating a reserve model by integrating the oil-gas-water interface model, the effective reservoir volume model, the pore volume model and the oil and gas volume model.
[0012] Based on the above implementation mode, the effective reservoir volume model is used to calculate the effective volume according to the product of the total rock volume and the sand-to-formation ratio; the pore volume model is used to calculate the porosity volume according to the product of the effective volume and the porosity; the oil and gas volume model is used to calculate the oil and gas volume according to the product of the porosity volume and the oil and gas saturation; the reserve model is used to calculate the reserves according to the oil and gas volume, volume coefficient and condensate oil / dissolved gas parameters.
[0013] In some embodiments, before generating the structural model according to the geological parameters, it also includes: based on high-resolution sequence stratigraphic theory, determining the relationship between core phase, logging phase and seismic phase according to the base level cycle and the accommodated space angle, and constructing a rock-electric-seismic response template.
[0014] The embodiment of the present specification also proposes a reservoir reserve prediction device, including: a geological parameter acquisition module, used to acquire the geological parameters of the target oil and gas field; the geological parameters include core data, logging data and seismic data; a structural model generation module, used to generate a structural model according to the geological parameters; the structural model is formed by matching the layer model and the fault model; the structural model is used to determine the stratigraphic relationship and the fault relationship; a phase model acquisition module, used to acquire the phase model through phase simulation based on the logging data; the phase model is used to indicate the distribution of the sand body; an attribute model construction module, used to construct an attribute model based on the phase simulation results corresponding to the logging data and the phase model; an oil and gas analysis module, used to determine the oil and gas system and the oil-gas-water interface through comprehensive reservoir geological analysis; the oil and gas system and the oil-gas-water interface are used to determine the reserve limit and reserve level; a reserve model construction module, used to construct a reserve model in combination with the structural model, phase model, attribute model, oil and gas system and the oil-gas-water interface; the reserve model is used to predict the oil and gas reserves of the target oil and gas field.
[0015] The embodiments of this specification also provide a computer-readable storage medium on which a computer program / instruction is stored. When the computer program / instruction is executed, it is used to implement the steps of the above-mentioned reservoir prediction method.
[0016] It can be seen from the technical solutions provided in the embodiments of this specification that the reservoir reserve prediction method in the embodiments of this specification uses core-logging-seismic data to fully explore the reservoir geological-logging-seismic response characteristics from the perspective of base level cycle and accommodating space, establish the core phase-logging phase-seismic correlation, solve the problem of insufficient geological theoretical basis in the existing modeling technology, and clarify that the basis for establishing the geological model is to clarify the reservoir geological evolution law in three-dimensional space and four-dimensional time domain. Secondly, with geological laws and logging data as hard data and seismic attributes as soft data, the relationship between sedimentary phase-physical properties, oil and gas content, and NTG-seismic attributes is analyzed to make up for the lack of actual data between wells or the strong heterogeneity of the reservoir in the existing technical solutions. The model and the actual formation are greatly different. Sequential inertial indication and sequential inertial Gauss are used for phase simulation and attribute simulation respectively, and seismic attributes are used for constraints to overcome the influence of faults on seismic data and make up for the lack of actual geological basis between wells. Thirdly, we made full use of various geological and geophysical data, combined rock-electricity-seismic data, and analyzed the relationship between sedimentary phases and physical properties, oil and gas content, and seismic attributes on the basis of clarifying the geological evolution law of the reservoir. We used sequence inertial indicators and sequence inertial Gaussian data to perform phase simulation and attribute simulation respectively, and calculated the geological reserves of oil and gas fields. In the case of severe lack of data in the initial stage of new project evaluation, the difference between the reserves disclosed publicly was 4%, and the results were able to meet the needs of new project evaluation. BRIEF DESCRIPTION OF THE DRAWINGS
[0017] In order to more clearly illustrate the embodiments of this specification or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this specification. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.
[0018] Figure 1 This is a flow chart of a reservoir prediction method according to an embodiment of this specification;
[0019] Figure 2 A schematic diagram of a seismic interpretation process according to an embodiment of this specification;
[0020] Figure 3 A schematic diagram of a process of generating a fault model according to an embodiment of this specification;
[0021] Figure 4 A schematic diagram of a flow chart of generating a construction model according to an embodiment of this specification;
[0022] Figure 5 A schematic diagram of a structural model-phase model-attribute model according to an embodiment of this specification;
[0023] Figure 6This is a schematic diagram of a sand body plane distribution according to an embodiment of this specification;
[0024] Figure 7 A schematic diagram of a reserve model according to an embodiment of this specification;
[0025] Figure 8 This is a module diagram of a reservoir prediction device according to an embodiment of this specification. DETAILED DESCRIPTION
[0026] The following will be combined with the drawings in the embodiments of this specification to clearly and completely describe the technical solutions in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on the embodiments in this specification, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this specification.
[0027] In order to solve the above technical problems, the embodiments of this specification propose a reservoir reserve prediction method. The method can be executed by a corresponding computing device, which includes but is not limited to at least one of a server, an industrial computer, and a PC. Figure 1 As shown, the reservoir reserve prediction method includes at least the following specific implementation steps.
[0028] S110: Acquire geological parameters of the target oil and gas field; the geological parameters include core data, well logging data and seismic data.
[0029] Geological parameters are data obtained through seismic waves or well logging, and are used in subsequent specific analysis processes.
[0030] Specifically, core data include core description, physical property analysis and diagenesis analysis, etc., well logging data include well logging las series, well logging interpretation and test data, etc., and seismic data include three-dimensional data volume, seismic interpretation and time-depth relationship, etc. The geological parameters can be obtained through stratigraphic division and comparison, sedimentary phase analysis, oil and gas reservoir analysis, well las, well logging interpretation, oil and gas testing, stratigraphic tracking, fault interpretation and depth domain grid after time-depth conversion. In practical applications, corresponding rock electroseismic data or other geological data can also be obtained by other methods, which are not limited.
[0031] In some embodiments, after obtaining the geological parameters, the relationship between core phases, logging phases and seismic phases, physical properties and oil and gas content can be analyzed from the perspective of base level cycles and accommodation space based on high-resolution sequence stratigraphy theory, and a rock-electric-seismic response template can be established to clarify the changes in the correlation between reservoir sedimentary phases, physical properties and oil and gas content during the base level rising or falling period, thereby assisting the subsequent data analysis and model building process.
[0032] S120: Generate a structural model according to the geological parameters; the structural model is formed by matching the layer model and the fault model; the structural model is used to determine the stratigraphic relationship and the fault relationship.
[0033] Since the structural model is formed by matching the layer model and the fault model, the layer model and the fault model can be generated first.
[0034] The layer model is generated by converting the time domain grid obtained from seismic interpretation into the depth domain through the relationship between time and depth on the well to form a stratigraphic layer grid that conforms to geological reality. First, the time domain grid and the longitudinal combination of plane polygons can be obtained based on the seismic interpretation data, and then the time domain is converted into the depth domain to obtain the layer model based on the correspondence between the time domain and depth. Specifically, the time domain grid obtained from seismic interpretation can be converted into the depth domain through the relationship between time and depth on the well to form a stratigraphic layer grid that conforms to geological reality, and then the layer model is determined based on the stratigraphic layer grid. This implementation process may involve steps such as layer grid determination, layer interpolation, and well-seismic layer matching. For example Figure 2 The figure shows a schematic diagram of the seismic interpretation process.
[0035] The fault model is formed by the longitudinal combination of plane polygons obtained by seismic interpretation to form a fault plane. The longitudinal combination of plane polygons is converted into a fault plane, and the truncation relationship is obtained through the fault plane. Then, the plane grid and the truncation relationship are matched to obtain the fault model. Specifically, the fault plane is formed by the longitudinal combination of plane polygons obtained by seismic interpretation, and the fault model is obtained by matching the plane grid on the basis of determining the truncation relationship between faults. This process may involve specific implementation steps such as fault combination, fault plane adjustment, and fault truncation. Figure 3 Figure 2 shows a schematic diagram of fault model generation.
[0036] After obtaining these two models, the layer model and fault model can be matched to form a well-seismic combined structural model, so as to determine the relationship between the strata and faults. The structural model can be carried out according to the triangular mesh modeling process in petrel, in which the stratigraphic data used is divided and compared according to the base level cycle theory. Figure 4 As shown, it is a schematic diagram of the process of constructing the model.
[0037] S130: Acquire a phase model through phase simulation based on the well logging data; the phase model is used to indicate the distribution status of the sand body.
[0038] The phase model is a three-dimensional model of sand body distribution obtained based on the well sedimentary phase, porosity and gas saturation data. In this model, gas indicates glacial-fluvial-delta phase sand bodies with excellent physical properties, poor gas indicates fluvial-delta phase sand bodies with good physical properties, gas&water indicates delta phase sand bodies with medium physical properties, and water indicates coastal and shallow marine muddy sand bodies with poor physical properties.
[0039] In order to obtain the phase model, the logging data can be coarsened into hard data; the hard data includes sedimentary phase data, logging interpretation data, porosity, hydrocarbon saturation and oil-gas layer sand-to-sand ratio. Then, the phase model can be obtained by phase simulation of the hard data and seismic data using random functions; the random functions include at least one of variogram, vertical scale and lateral probability setting. Specifically, the phase model can be obtained by simulating the multi-phase three-dimensional geological distribution characteristics using the sequential inertial indicator algorithm and attribute constraints. The obtained phase model is a model for verifying the cyclic changes of the base level.
[0040] S140: Constructing an attribute model based on the well logging data and the phase simulation results corresponding to the phase model.
[0041] The attribute model is obtained based on the attributes of the seismic data volume. The logging data can be coarsened into hard data; the hard data includes sedimentary phase data, logging interpretation data, porosity, hydrocarbon saturation and oil and gas layer sand-land. The seismic data is obtained as soft data based on the attributes of the seismic data volume, and the geological relationship is determined based on the hard data and soft data; the geological relationship includes sedimentary phase-physical property, hydrocarbon content, oil and gas layer sand-land ratio-seismic attribute relationship. Finally, the attribute model is constructed based on the geological relationship; the attribute model includes porosity, hydrocarbon saturation and oil and gas layer sand-land ratio models that conform to the base level cycle changes.
[0042] Specifically, when constructing the attribute model, the sequential Gaussian algorithm, seismic attributes and sedimentary phase constraints can be used to simulate the three-dimensional geological distribution of physical properties, oil and gas content and oil and gas layer sand-to-land ratio, and the attribute model can be constructed based on the three-dimensional geological distribution of physical properties, oil and gas content and oil and gas layer sand-to-land ratio. Figure 5 Shown is a schematic diagram of the generated structural model-phase model-property model.
[0043] Specifically, the root mean square amplitude (RMS) has obvious reflection characteristics for a variety of sandstones and mudstones, and can indicate the planar distribution of the above-mentioned sedimentary sand bodies. Taking the RMS planar trend as a constraint, the logging interpretation porosity and gas saturation data are used as hard data to simulate the reservoir space porosity and oil and gas saturation. Sequential Gaussian is used to match sedimentary phases-physical properties, oil and gas properties, and NTG-seismic attributes, and to simulate porosity, oil and gas saturation, and NTG, and obtain the porosity, oil and gas saturation, and NTG models that conform to the base level cycle changes. The two are interconnected, complement each other, and confirm each other. Figure 6 As shown, generally, glacial-fluvial-deltaic sand bodies have high porosity, high oil and gas saturation, and high NTG content; coastal shallow-marine muddy sand bodies have low porosity, low oil and gas saturation, and low NTG content.
[0044] S150: Comprehensive reservoir geological analysis to determine the oil and gas system and the oil, gas and water interface; the oil and gas system and the oil, gas and water interface are used to determine the reserve limit and reserve level.
[0045] The oil and gas system and the oil, gas and water interface are used to determine the 3P reserve limit and reserve level. Based on the well logging interpretation and oil test analysis results, the 1P and 3P limits are determined by the bottom of the oil and gas layer and the top of the water layer, and half of the two is the 2P limit. Figure 5 Shown is a schematic diagram for determining the oil and gas system and the oil-gas-water interface.
[0046] Correspondingly, the oil / gas-water boundary can be determined and the oil-gas-water interface model can be established based on the oil and gas reservoir profile analysis.
[0047] S160: Constructing a reserve model by combining the structural model, phase model, property model, oil and gas system and oil-gas-water interface; the reserve model is used to predict the oil and gas reserves of the target oil and gas field.
[0048] Based on the above processing results, the oil-gas-water interface model, effective reservoir volume model, pore volume model and oil and gas volume model can be constructed respectively, and then the oil-gas-water interface model, effective reservoir volume model, pore volume model and oil and gas volume model can be combined to generate a reserve model.
[0049] In some embodiments, the effective reservoir volume model is used to calculate the effective volume based on the product of the total rock volume and the sand-to-formation ratio; the pore volume model is used to calculate the porosity volume based on the product of the effective volume and the porosity; the oil and gas volume model is used to calculate the oil and gas volume based on the product of the porosity volume and the oil and gas saturation; the reserve model is used to calculate the reserves based on the oil and gas volume, volume coefficient, condensate oil parameters, and solution gas parameters.
[0050] The specific calculation formulas of different models are as follows, among which, effective volume model (Net volume) = Bulk volume × sand-to-ground ratio NTG; pore volume model (Pore volume) = Net volume × porosity; hydrocarbon volume model (HCPV) = Pore volum × hydrocarbon saturation (So or Sg); hydrocarbon reserve model (GIIP / STOIIP) = HCPV / (volume coefficient Bo or Bg) + condensate oil / dissolved gas.
[0051] Based on the introduction of the above embodiments, a specific scenario example is used for further explanation. Reservoir modeling and geological reserve evaluation were carried out for the Cambrian-Ordovician-Devonian in Area A of Algeria in northern Africa. The strata in Area A experienced two large-scale transgressions. At the end of the Ordovician, due to its location near the Antarctic, it experienced an ice age and developed glacial rocks. From bottom to top, the sedimentary environments are Cambrian continental rivers, Early Ordovician coastal shallow sea-braided river delta deposition, Middle Ordovician shallow sea-deep sea deposition, Late Ordovician braided river delta-onshore rivers, glacial deposition, Silurian extensive development of marine mudstones, Early Devonian delta-coastal shallow sea deposition, Late Devonian coastal shallow sea-delta deposition. The existing methods have obvious problems of insufficient basis for the vertical and planar distribution of reservoirs and the prediction of inter-well reservoirs. Sedimentary reservoir analysis based on base level cycles can better interpret the distribution law of reservoirs in various strata. The lateral prediction based on seismic attributes is sufficient, which can achieve objective evaluation goals and meet the needs of new project asset evaluation and oil and gas field development.
[0052] ① For the target oil and gas fields to be evaluated, collect geological, logging and seismic data, including stratigraphic division and comparison, sedimentary phase analysis, oil and gas reservoir analysis, well Las, logging interpretation, oil and gas testing, stratigraphic tracing, fault interpretation and depth domain grid after time-depth conversion, and all other rock seismic data that can be collected, as well as relevant data from testing and analysis, to form the rock seismic response characteristics within the base level cycle framework, and clarify the associated changes in reservoir sedimentary phases, physical properties and oil and gas properties during the base level rise or fall period;
[0053] ② On the basis of the depth domain layer and fault data of seismic interpretation, the layer, fault and structural models are established in sequence, including layer grid determination, layer interpolation, well-seismic layer matching, fault combination, fault plane adjustment, fault cutting, formation-layer matching, structural skeleton establishment and structural layer subdivision, so as to establish a structural model combining well-seismic and fault-seismic analysis;
[0054] ③ Introduce conditional functions to calculate the sand-to-ground ratio (NTG) of oil and gas layers, coarsen the well data, including sedimentary facies, logging interpretation, porosity, oil and gas saturation and NTG, establish random functions, including variogram, vertical ratio and lateral probability settings, select seismic attribute constraints, including layer attributes and body attributes, use sequence inertial indications for facies simulation, and obtain a facies model that conforms to the cyclic changes of the base level. In this model, gas indicates glacial-river-delta facies sand bodies with excellent physical properties, poor gas indicates river-delta facies sand bodies with good physical properties, gas & water indicates delta facies sand bodies with medium physical properties, and water indicates coastal shallow-sea muddy sand bodies with poor physical properties;
[0055] ④ Coarsening well data porosity, oil and gas saturation and NTG as hard data; based on the phase simulation results, seismic attribute constraints are selected as soft data; in this study, the root mean square amplitude (RMS) has obvious reflection characteristics for various sandstones and mudstones, which can indicate the planar distribution of the above-mentioned various sedimentary sand bodies. Sequential Gaussian is used to match sedimentary phases-physical properties, oil and gas properties, and NTG-seismic attributes, and to simulate porosity, oil and gas saturation and NTG to obtain a porosity, oil and gas saturation and NTG model that conforms to the cyclic changes of the base level; generally, glacial-river-delta phase sand bodies have high porosity, high oil and gas saturation, high NTG content, and seismic attributes show red strip distribution; shallow-shore muddy sand bodies have low porosity, low oil and gas saturation, low NTG content, and seismic attributes show purple patch distribution. Figure 7 Shown is a schematic diagram of the comparison of Upper / Middle / Lower Ordovician sedimentary phases and porosity simulation.
[0056] ⑤ Based on the analysis of the oil and gas reservoir profile, determine the oil / gas-water boundary, establish the oil-gas-water interface model, and simulate the total volume (Bulk volume), effective volume (Net volume), pore volume (Pore volume) and hydrocarbon-containing volume (HCPV), and finally obtain the reserve model of the evaluation target block.
[0057] Through the introduction of the above embodiments and scenario examples, it can be seen that the method uses core-logging-seismic data, from the perspective of base level cycle and accommodating space, to fully explore the reservoir geological-logging-seismic response characteristics in principle, establish the core phase-logging phase-seismic correlation, solve the problem of insufficient geological theoretical basis in the existing modeling technology, and clarify that the basis for establishing the geological model is to clarify the reservoir geological evolution law in three-dimensional space and four-dimensional time domain. Secondly, with geological laws and logging data as hard data and seismic attributes as soft data, the relationship between sedimentary phase-physical properties, oil and gas content, and NTG-seismic attributes is analyzed to make up for the lack of actual data between wells or the strong heterogeneity of the reservoir in the existing technical solutions. The model and the actual formation are greatly different. Sequential inertial indication and sequential inertial Gauss are used for phase simulation and attribute simulation respectively, and seismic attributes are used for constraints, which overcomes the influence of faults on seismic data and makes up for the lack of actual geological basis between wells. Thirdly, we made full use of various geological and geophysical data, combined rock-electricity-seismic data, and analyzed the relationship between sedimentary phases and physical properties, oil and gas content, and seismic attributes on the basis of clarifying the geological evolution law of the reservoir. We used sequence inertial indicators and sequence inertial Gaussian data to perform phase simulation and attribute simulation respectively, and calculated the geological reserves of oil and gas fields. In the case of severe lack of data in the initial stage of new project evaluation, the difference between the reserves disclosed publicly was 4%, and the results were able to meet the needs of new project evaluation.
[0058] Based on the above reservoir reserve prediction method, the present specification also proposes a reservoir reserve prediction device. Figure 8 As shown, the reservoir reserve prediction device includes the following specific modules.
[0059] The geological parameter acquisition module 810 is used to acquire the geological parameters of the target oil and gas field; the geological parameters include core data, well logging data and seismic data.
[0060] The structural model generation module 820 is used to generate a structural model according to the geological parameters; the structural model is formed by matching the layer model and the fault model; the structural model is used to determine the stratigraphic relationship and the fault relationship.
[0061] The phase model acquisition module 830 is used to acquire a phase model through phase simulation based on well logging data; the phase model is used to indicate the distribution status of sand bodies.
[0062] The attribute model building module 840 is used to build an attribute model based on the well logging data and the phase simulation results corresponding to the phase model.
[0063] The oil and gas analysis module 850 is used to determine the oil and gas system and the oil-gas-water interface through comprehensive reservoir geological analysis; the oil and gas system and the oil-gas-water interface are used to determine the reserve limit and reserve level.
[0064] The reserve model building module 860 is used to build a reserve model by combining the structural model, phase model, attribute model, oil and gas system and oil-gas-water interface; the reserve model is used to predict the oil and gas reserves of the target oil and gas field.
[0065] The embodiments of this specification provide a computer-readable storage medium on which a computer program / instruction is stored. The computer-readable storage medium can be read by a processor based on an internal bus of a device, and the program instructions in the computer-readable storage medium are then implemented by the processor.
[0066] In this embodiment, the computer-readable storage medium can be implemented in any appropriate manner. The computer-readable storage medium includes, but is not limited to, random access memory (RAM), read-only memory (ROM), cache, hard disk drive (HDD), memory card, etc. The computer storage medium stores computer program instructions. When the computer program instructions are executed, the present specification is implemented. Figure 1 The program instructions or modules of the reservoir reserve prediction method of the corresponding embodiment.
[0067] It should be noted that the reservoir reserve prediction method, device and storage medium can be applied to the field of geological exploration and development technology, and can also be applied to other technical fields except the field of geological exploration and development technology, without limitation.
[0068] Although the process flows described above include multiple operations that occur in a particular order, it should be clearly understood that the processes may include more or fewer operations, which may be performed sequentially or in parallel (eg, using parallel processors or a multi-threaded environment).
[0069] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present specification. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.
[0070] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.
[0071] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.
[0072] Those skilled in the art will appreciate that the embodiments of this specification may be provided as methods, systems or computer program products. Therefore, the embodiments of this specification may take the form of complete hardware embodiments, complete software embodiments or embodiments combining software and hardware. Moreover, the embodiments of this specification may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.
[0073] The present specification embodiments may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present specification embodiments may also be practiced in distributed computing environments where tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules may be located in local and remote computer storage media, including storage devices.
[0074] Each embodiment in this specification is described in a progressive manner, and the same and similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment. In the description of this specification, the description of the reference terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the embodiment of this specification. In this specification, the schematic representation of the above terms does not necessarily target the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner. In addition, in the absence of contradiction, a person skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.
[0075] The above is only an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.
Claims
1. A reservoir reserve prediction method, characterized in that: include: Obtaining geological parameters of the target oil and gas field; the geological parameters include core data, well logging data and seismic data; generating a structural model according to the geological parameters; The structural model is formed by matching the layer model and the fault model; the structural model is used to determine the relationship between the strata and the faults; Acquire a phase model through phase simulation based on well logging data; the phase model is used to indicate the distribution of sand bodies; Constructing an attribute model based on well logging data and facies simulation results corresponding to the facies model; Comprehensive reservoir geological analysis determines the oil and gas system and the oil, gas and water interface; the oil and gas system and the oil, gas and water interface are used to determine the reserve limit and reserve level; A reserve model is constructed by combining the structural model, phase model, property model, oil and gas system and oil-gas-water interface; the reserve model is used to predict the oil and gas reserves of the target oil and gas field.
2. The method according to claim 1, characterized in that The core data includes at least one of core description, physical property analysis and diagenesis analysis; the logging data includes at least one of logging LAS series data, logging interpretation data and test data; the seismic data includes at least one of three-dimensional data volume, seismic interpretation data and time-depth relationship.
3. The method according to claim 2, characterized in that The step of generating a structural model according to the geological parameters comprises: Based on the seismic interpretation data, the time domain grid and the plane polygon longitudinal combination are obtained respectively; Combining the correspondence between the time domain and the depth, the time domain is converted into the depth domain to obtain a layer model; the layer model includes a layer grid; The plane polygons are longitudinally combined and converted into fault planes; the fault planes have corresponding truncation relationships; Matching the layer grid and the truncation relationship to obtain a fault model; The layer model and the fault model are matched to form the structural model.
4. The method according to claim 1, characterized in that The method of obtaining a phase model through phase simulation based on well logging data includes: The roughened logging data is hard data; the hard data includes sedimentary facies data, logging interpretation data, porosity, oil and gas saturation and oil and gas layer sand-to-soil ratio; The hard data and seismic data are subjected to phase simulation using a random function to obtain a phase model; the random function includes at least one of a variogram, a vertical scale, and a lateral probability setting.
5. The method according to claim 1, characterized in that The method of constructing the attribute model based on the well logging data and the phase simulation results corresponding to the phase model includes: The roughened logging data is hard data; the hard data includes sedimentary facies data, logging interpretation data, porosity, oil and gas saturation and oil and gas layer sand-to-soil ratio; Seismic data is obtained as soft data according to the attributes of the seismic data volume layer; Determine geological relationships based on the hard data and soft data; the geological relationships include sedimentary facies-physical properties, oil and gas content, oil and gas layer sand-to-seismic attribute relationships; An attribute model is constructed based on the geological relationship; the attribute model includes a porosity, oil and gas saturation and oil and gas layer sand-to-formation ratio model that conforms to the base level cycle change.
6. The method according to claim 5, characterized in that The constructing of the attribute model based on the geological relationship comprises: Simulate the three-dimensional geological distribution of physical properties, hydrocarbon content and oil-gas layer-sand ratio using the sequential Gaussian algorithm, seismic attributes and sedimentary facies constraints; An attribute model is constructed based on the three-dimensional geological distribution of the physical properties, oil and gas content, and oil and gas layer sand-to-soil ratio.
7. The method according to claim 1, characterized in that The construction of the reserve model by combining the structural model, phase model, property model, oil and gas system and oil-gas-water interface includes: Based on the phase model, the property model, the oil-gas system and the oil-gas-water interface, an oil-gas-water interface model, an effective reservoir volume model, a pore volume model and an oil-gas volume model are respectively established; The oil-gas-water interface model, the effective reservoir volume model, the pore volume model and the oil and gas volume model are integrated to generate a reserve model.
8. The method according to claim 7, characterized in that The effective reservoir volume model is used to calculate the effective volume according to the product of the total rock volume and the sand-to-formation ratio; The pore volume model is used to calculate the porosity volume based on the product of the effective volume and the porosity; The oil and gas volume model is used to calculate the oil and gas volume according to the product of the porosity volume and the oil and gas saturation; The reserve model is used to calculate the reserves based on the oil and gas volume, volume coefficient, condensate oil parameters, and solution gas parameters.
9. The method according to claim 1, characterized in that Before generating the structural model according to the geological parameters, the method further comprises: Based on high-resolution sequence stratigraphy theory, the relationship between core phase, logging phase and seismic phase is determined according to the base-level cycle and the angle of accommodation space, and a rock-electric-seismic response template is constructed.
10. A reservoir reserve prediction device, characterized in that: include: A geological parameter acquisition module is used to acquire geological parameters of a target oil and gas field; the geological parameters include core data, well logging data and seismic data; A structural model generation module, used to generate a structural model according to the geological parameters; the structural model is formed by matching the layer model and the fault model; the structural model is used to determine the relationship between the strata and the faults; A phase model acquisition module is used to acquire a phase model through phase simulation based on well logging data; the phase model is used to indicate the distribution of sand bodies; An attribute model building module is used to build an attribute model based on well logging data and phase simulation results corresponding to the phase model; The oil and gas analysis module is used to determine the oil and gas system and the oil-gas-water interface through comprehensive reservoir geological analysis; the oil and gas system and the oil-gas-water interface are used to determine the reserve limit and reserve level; The reserve model building module is used to build a reserve model by combining the structural model, phase model, attribute model, oil and gas system and oil-gas-water interface; the reserve model is used to predict the oil and gas reserves of the target oil and gas field.
11. A computer-readable storage medium having a computer program / instruction stored thereon, characterized in that: The computer program / instructions, when executed, are used to implement the steps of the method according to any one of claims 1 to 9.