A method and system for quantitative characterization of deep-water sediments based on stratigraphic forward modeling

Abstract

The present application discloses a method and system for quantitative characterization of deep-water sediments based on stratigraphic forward modeling, and relates to the technical field of deep-water sediment forward modeling and quantitative analysis. The method comprises obtaining geological data of a target area, analyzing sedimentary characteristics according to the geological data, and constructing a regional geological concept model; determining key input parameters required for stratigraphic forward modeling according to the regional geological concept model; performing forward modeling of deep-water sedimentary strata according to the key input parameters by using a method of coupling hydrodynamic equations and fuzzy logic rules, and establishing a quantitative model of deep-water sedimentary strata; performing rationality analysis on the quantitative model of deep-water sedimentary strata, quantitatively characterizing the deep-water sedimentary strata, and improving the deep-water sedimentary model. The present application can quantitatively characterize the deep-water sedimentary strata and improve the deep-water sedimentary model.

Description

Technical Field

[0001] The present application relates to the technical field of deep-water sediment forward modeling and quantitative analysis, and in particular to a method and system for quantitative characterization of deep-water sediment based on stratum forward modeling. Background Art

[0002] Deepwater oil and gas exploration and development has gradually become an important part of oil and gas exploration and development, and its importance to the exploration and development of deepwater oil and gas resources is becoming increasingly significant. However, there are challenges in the process of deepwater oil and gas exploration in terms of technology, safety, economy, and acquisition of geological data. In the case of limited geological data, forward simulation of sedimentary stratigraphy for deepwater deposition has the characteristics of low economic cost, fast response speed, and accurate model results. Carrying out relevant research can effectively promote deepwater oil and gas exploration and development. In addition, there are rich types of deepwater sediments, including turbidity current deposits, pelagic and semi-pelagic deposits, contour flow deposits, and block transport bodies. The sedimentary processes of different deepwater deposits are different, and hydrodynamic equations alone cannot be used to effectively simulate all of them. At present, the forward simulation research on deepwater deposition usually focuses on source-sink systems, submarine fan systems, gravity flow deposits, and contour flow deposits simulations using hydrodynamic equations as simulation methods, and there is a lack of simulation research on deepwater deposition.

[0003] In summary, the current existing technology is insufficient in the quantitative characterization of deep-water sedimentation based on sediment forward simulation, the deep-water sedimentation model is insufficient, and there is a lack of methods for simulating and quantitatively characterizing deep-water sedimentation. Therefore, how to provide a deep-water sedimentation quantitative characterization method that can quantitatively characterize deep-water sedimentary strata and improve deep-water sedimentation models has become a technical problem that needs to be solved urgently in this field. Summary of the invention

[0004] The purpose of this application is to provide a method and system for quantitative characterization of deep-water sediments based on stratigraphic forward modeling, which can quantitatively characterize deep-water sedimentary strata and improve deep-water sedimentary models.

[0005] To achieve the above objectives, this application provides the following solutions.

[0006] In a first aspect, the present application provides a method for quantitative characterization of deep-water sediments based on stratigraphic forward modeling, and the method for quantitative characterization of deep-water sediments based on stratigraphic forward modeling includes the following steps.

[0007] Obtain geological data of the target area, analyze sedimentary characteristics based on the geological data, and construct a regional geological conceptual model.

[0008] According to the regional geological conceptual model, key input parameters required for stratigraphic forward modeling are determined; the key input parameters include initial sedimentary paleo-geomorphology, changes in sediment accommodation space, sea level changes, sediment properties and sediment provenance parameters.

[0009] According to the key input parameters, a method of coupling hydrodynamic equations and fuzzy logic rules is used to perform forward simulation of deep-water sedimentary strata and establish a quantitative model of deep-water sedimentary strata; the method of coupling hydrodynamic equations and fuzzy logic rules refers to an algorithm for simulating and establishing the quantitative model of deep-water sedimentary strata obtained by coupling hydrodynamic equations with fuzzy logic rules according to the source, sedimentation process and sediment type of deep-water sediments; the quantitative model of deep-water sedimentary strata includes spatial distribution information and acceptable spatial change information of sediments of different particle sizes during the simulation time.

[0010] The rationality of the deep-water sedimentary stratum quantitative model is analyzed to quantitatively characterize the deep-water sedimentary stratum and improve the deep-water sedimentary model.

[0011] Optionally, geological data of the target area are obtained, and sedimentary characteristics are analyzed based on the geological data to construct a regional geological conceptual model, which specifically includes the following steps.

[0012] Through literature research, the previous geological research results of the target area are determined to form a basic geological understanding of the target area.

[0013] Obtain the geological data of the target area; the geological data includes seismic data, well logging data, core data, field outcrop data and geochemical analysis and test data of the target area.

[0014] Based on the geological data and basic geological knowledge of the target area, the geological characteristics of the target area are analyzed, the characteristics of the sedimentary strata are characterized, and a regional geological conceptual model is established.

[0015] Optionally, based on the regional geological conceptual model, key input parameters required for stratigraphic forward modeling are determined, which specifically includes the following steps.

[0016] According to the regional geological conceptual model, the geological data and the basic geological knowledge of the target area, the key input parameters required for stratigraphic forward modeling are restored to obtain the key input parameters.

[0017] Optionally, after the step of determining key input parameters required for stratigraphic forward modeling according to the regional geological conceptual model, the method for quantitative characterization of deep-water sediments based on stratigraphic forward modeling further includes the following steps.

[0018] A parameter sensitivity analysis is performed on the key input parameters to obtain the key input parameters after the parameter sensitivity analysis; the key input parameters after the parameter sensitivity analysis are used as the key input parameters, and a method of coupling hydrodynamic equations and fuzzy logic rules is used to perform forward simulation of deep-water sedimentary formations, so as to establish a quantitative model of the deep-water sedimentary formations.

[0019] Optionally, according to the key input parameters, a method of coupling hydrodynamic equations and fuzzy logic rules is used to perform forward simulation of deep-water sedimentary strata and establish a quantitative model of deep-water sedimentary strata, which specifically includes the following steps.

[0020] Based on the method of coupling hydrodynamic equations and fuzzy logic rules, the key input parameters are input into Sedfill3D sedimentary stratum forward modeling software, and solved and simulated by Sedfill3D sedimentary stratum forward modeling software to obtain the quantitative model of deep-water sedimentary strata.

[0021] Optionally, a rationality analysis is performed on the quantitative model of the deep-water sedimentary strata, the deep-water sedimentary strata are quantitatively characterized, and the deep-water sedimentary pattern is improved, which specifically includes the following steps.

[0022] Based on the geological data, rationality analysis data of the target area are determined, wherein the rationality analysis data include well logging gamma curve data, three-dimensional seismic profile data and lithofacies combination sequence data.

[0023] The rationality analysis data is compared with the single well virtual gamma curve output by the deep-water sedimentary stratum quantitative model and the sedimentary stratum filling profiles of each sedimentary period to determine the matching degree of the deep-water sedimentary stratum quantitative model.

[0024] According to the matching degree and matching degree threshold of the deep-water sedimentary stratum quantitative model, a rationality analysis result of the matching degree of the deep-water sedimentary stratum quantitative model is determined.

[0025] A quantitative analysis of sedimentary characteristics is performed on the deep-water sedimentary stratum quantitative model whose matching degree is greater than or equal to the matching degree threshold to obtain a quantitative analysis result of sedimentary characteristics; the quantitative analysis result of sedimentary characteristics includes sedimentary thickness, sand-to-formation ratio, single well virtual gamma curve, vertical lithofacies combination and planar sedimentary facies characteristics.

[0026] The deepwater sedimentation pattern is determined based on the quantitative analysis results of the sedimentary characteristics; the deepwater sedimentation pattern includes a submarine fan sedimentation pattern dominated by gravity flow deposition and containing deepwater suspended deposition.

[0027] Optionally, the single-well virtual gamma curve is a gamma curve generated by applying single-well mud content data, and the calculation formula adopted is the following formula.

[0028] ;

[0029] Among them, GR is the gamma value corresponding to the generated single well virtual gamma curve, is the output single well mud content, is the actual maximum gamma value of the control well, is the minimum gamma value of the actual control well.

[0030] Optionally, the deposition thickness is calculated using the following formula.

[0031] ;

[0032] ;

[0033] in, is the sediment thickness during a deposition period with t simulation time steps, t represents the tth simulation time step, is the sediment volume per unit grid, i represents the i-th unit grid, A is the simulation range of the target area, is the total deposition thickness.

[0034] Optionally, the matching degree threshold is 80%.

[0035] In a second aspect, the present application provides a system for quantitative characterization of deep-water deposits based on stratigraphic forward modeling, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method for quantitative characterization of deep-water deposits based on stratigraphic forward modeling described in the first aspect.

[0036] According to the specific embodiments provided in this application, this application has the following technical effects:

[0037] The present application provides a method and system for quantitative characterization of deepwater sediments based on stratigraphic forward modeling. First, a regional geological conceptual model is constructed based on geological data, and the key input parameters required for stratigraphic forward modeling are determined based on the regional geological conceptual model. After the key input parameters are determined, a deepwater sedimentary stratum forward modeling is performed by coupling the hydrodynamic equation with the fuzzy logic rule method, thereby establishing a deepwater sedimentary stratum quantitative model. By fully considering the source, sedimentation process and sediment type of deepwater sediments, the principle of the hydrodynamic equation and the principle of the fuzzy logic rule are effectively coupled, thereby establishing the deepwater sedimentary stratum quantitative model, and then the deepwater sedimentary stratum quantitative model can be used to quantitatively characterize the deepwater sedimentary strata, improve the deepwater sedimentary model, and make up for the current lack of research work related to deepwater sedimentary forward modeling, which has important practical significance for deepwater oil and gas exploration and development. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0039] Figure 1 This is a flow chart of a method for quantitative characterization of deep-water sediments based on stratigraphic forward modeling provided in one embodiment of the present application.

[0040] Figure 2 A graph showing changes in the pelagic-semi-pelagic sedimentation rate provided in one embodiment of the present application.

[0041] Figure 3 A diagram showing changes in the distribution range of pelagic-semi-pelagic sediment development provided in one embodiment of the present application.

[0042] Figure 4 This is a comparison diagram of the actual control well gamma curve and the single well virtual gamma curve provided in one embodiment of the present application.

[0043] Figure 5 This is a flow chart of a method for coupling hydrodynamic equations and fuzzy logic rules provided in one embodiment of the present application. DETAILED DESCRIPTION

[0044] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0045] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0046] like Figure 1 As shown, this embodiment proposes a method for quantitative characterization of deep-water sediments based on stratigraphic forward modeling, and the method for quantitative characterization of deep-water sediments based on stratigraphic forward modeling specifically includes the following steps.

[0047] Step S1: Acquire geological data of the target area, analyze sedimentary characteristics based on the geological data, and construct a regional geological conceptual model.

[0048] In this embodiment, step S1 obtains geological data of the target area, analyzes sedimentary characteristics based on the geological data, and constructs a regional geological conceptual model, which specifically includes the following steps.

[0049] Step S11: Determine the previous geological research results of the target area through literature research to form a basic geological understanding of the target area.

[0050] Step S12, obtaining the geological data of the target area; the geological data includes seismic data, well logging data, core data, field outcrop data and geochemical analysis test data of the target area.

[0051] Step S13: Analyze the geological characteristics of the target area based on the geological data and basic geological knowledge of the target area, characterize the characteristics of the sedimentary strata, and establish the regional geological conceptual model.

[0052] In this embodiment, establishing a regional geological conceptual model includes the following contents.

[0053] Literature survey of previous research results to form a basic geological understanding of the target area, including research results such as deepwater sediment types, source-sink analysis, reservoir distribution patterns, related sedimentary patterns, and deepwater sedimentary characteristics and formation mechanisms in the target area. Combined with geological data such as seismic data, well logging data, core data, field outcrop data, and geochemical analysis and test data, the geological characteristics of the target area are analyzed. Seismic data are used to construct the stratigraphic framework of the target area, well logging data to determine the sedimentary components and single well phase sedimentary characteristics, and core and geochemical analysis and test data to clarify the hydrodynamic conditions and physical and chemical properties of sediments. The regional geological concept model is established by integrating the geological understanding formed through literature survey and various data obtained based on geological data analysis. The regional geological concept model is the integration and summary of the above-mentioned various information and data, and is used to restore the key input parameters of stratigraphic forward simulation.

[0054] Step S2: Determine the key input parameters required for stratigraphic forward modeling based on the regional geological conceptual model, wherein the key input parameters include initial sedimentary paleo-geomorphology, changes in sediment accommodation space, sea level changes, sediment properties, and sediment provenance parameters.

[0055] In this embodiment, step S2 determines the key input parameters required for stratigraphic forward modeling according to the regional geological conceptual model, and specifically includes the following steps.

[0056] According to the regional geological conceptual model, the geological data and the basic geological knowledge of the target area, the key input parameters required for stratigraphic forward modeling are restored to obtain the key input parameters.

[0057] In this embodiment, after the step S2 of determining the key input parameters required for stratigraphic forward modeling according to the regional geological conceptual model, the method for quantitative characterization of deep-water sediments based on stratigraphic forward modeling further includes the following steps.

[0058] A parameter sensitivity analysis is performed on the key input parameters to obtain the key input parameters after the parameter sensitivity analysis. The key input parameters after the parameter sensitivity analysis are used as the key input parameters to perform forward simulation of deep-water sedimentary formations by using a method of coupling hydrodynamic equations and fuzzy logic rules, so as to establish a quantitative model of the deep-water sedimentary formations.

[0059] In this embodiment, the key input parameters required for the forward simulation of the recovery formation include the following.

[0060] On the basis of the established regional geological conceptual model, combined with basic geological understanding, the key input parameters required for the simulation are restored, including: the initial paleogeomorphology and simulation scale range of sedimentary simulation based on seismic data recovery, sea level changes based on literature research and regional sedimentary phase recovery, application of tectonic subsidence data to restore the changes in sediment accommodation space, logging data and cores to restore sediment properties and sediment source parameters, etc., simulation time and fluid sampling interval are restored according to geological age information, in preparation for the next step of sedimentary forward simulation.

[0061] Step S3, according to the key input parameters, the method of coupling hydrodynamic equations and fuzzy logic rules is used to perform forward simulation of deep-water sedimentary strata, and establish a quantitative model of deep-water sedimentary strata. Among them, the method of coupling hydrodynamic equations and fuzzy logic rules refers to an algorithm for simulating and establishing the quantitative model of deep-water sedimentary strata obtained by coupling hydrodynamic equations with fuzzy logic rules according to the source, sedimentation process and sediment type of deep-water sediments. The quantitative model of deep-water sedimentary strata is a model used to quantitatively characterize deep-water sedimentary strata in order to improve the deep-water sedimentation pattern. The quantitative model of deep-water sedimentary strata includes spatial distribution information and permissible spatial variation information of sediments of different particle sizes during the simulation time.

[0062] In this embodiment, step S3 performs forward simulation of deep-water sedimentary formations according to the key input parameters by coupling hydrodynamic equations with fuzzy logic rules to establish a quantitative model of deep-water sedimentary formations, which specifically includes the following steps.

[0063] Based on the method of coupling hydrodynamic equations and fuzzy logic rules, the key input parameters are input into Sedfill3D sedimentary stratum forward modeling software, and the quantitative model of the deep-water sedimentary stratum is obtained by solving and simulating the software.

[0064] In this embodiment, the hydrodynamic equations and fuzzy logic rules include the following contents.

[0065] The hydrodynamic equation is based on the principles of conservation of mass and momentum, and uses the simplified Navier-Stokes hydrodynamic equation. It comprehensively considers various geological processes, and calculates the motion state of the fluid and its contact relationship with the terrain, which is more in line with the actual situation and can simulate the erosion, transportation and deposition of sediments. The fuzzy logic rule is based on the traditional Boolean logic theory, which can quantify qualitative geological data and integrate it into the simulation process. It consists of fuzzy sets and fuzzy rules, which simplifies the uncertainty problem in the simulation process and has a faster simulation speed.

[0066] In this embodiment, the method of coupling the hydrodynamic equations with the fuzzy logic rules includes the following contents.

[0067] Based on the different sources, sedimentary processes and sediment types of deep-water sediments, the hydrodynamic equations and fuzzy logic rules are effectively coupled, the key input parameters recovered above are input into the Sedfill3D sedimentary stratum forward simulation software, and the boundary condition constraints are set according to the parameters such as the simulation target area range and the simulation time step. The Sedfill3D sedimentary stratum forward simulation software is run on the computer to calculate and solve and simulate the deep-water sedimentary process with different sedimentary dynamics mechanisms, and the deep-water sedimentary stratum quantitative model is obtained and the deep-water sedimentary three-dimensional spatiotemporal distribution data volume is output. The hydrodynamic equation can effectively simulate the source-sink system and the submarine fan system quantitatively, but it cannot simulate deep-water suspended sedimentation. The application of fuzzy logic rules to simulate deep-water suspended sedimentation can effectively solve this problem. Therefore, for different deep-water sedimentary processes, a method of coupling hydrodynamic equations and fuzzy logic rules is established to carry out sedimentation forward simulation, and the obtained deep-water sedimentary stratum quantitative model has stronger authenticity and effectiveness.

[0068] Step S4: performing rationality analysis on the deepwater sedimentary stratum quantitative model, quantitatively characterizing the deepwater sedimentary stratum, and improving the deepwater sedimentary model.

[0069] In this embodiment, step S4 performs rationality analysis on the deep-water sedimentary stratum quantitative model, quantitatively characterizes the deep-water sedimentary stratum, and improves the deep-water sedimentary model, which specifically includes the following steps.

[0070] Step S41, determining rationality analysis data of the target area according to the geological data, wherein the rationality analysis data includes well logging gamma curve data, three-dimensional seismic profile data and lithofacies combination sequence data.

[0071] Step S42: Compare the rationality analysis data with the single well virtual gamma curve and the sedimentary stratum filling profiles of each sedimentary period output by the deep-water sedimentary stratum quantitative model to determine the matching degree of the deep-water sedimentary stratum quantitative model.

[0072] Step S43: Determine a rationality analysis result of the matching degree of the deep-water sedimentary stratum quantitative model according to the matching degree and matching degree threshold of the deep-water sedimentary stratum quantitative model.

[0073] In this embodiment, the matching threshold can be set to 80%. By looping steps S1 to S3, multiple deep-water sedimentary strata quantitative models can be established, and the matching value of each deep-water sedimentary strata quantitative model is determined according to step S42. The matching value reflects the matching degree between the single well virtual gamma curve output by the deep-water sedimentary strata quantitative model and the filling profile of the sedimentary strata in each sedimentary period and the actual data in the geological data. If the matching value of the current deep-water sedimentary strata quantitative model is less than 80%, it is determined that the matching degree of the current deep-water sedimentary strata quantitative model is low, and the result obtained when finally characterizing the deep-water sedimentary strata and improving the deep-water sedimentary model is inaccurate. Therefore, the deep-water sedimentary stratum quantitative model is eliminated. If the matching value of the current deep-water sedimentary stratum quantitative model is greater than or equal to 80%, it is determined that the matching degree of the current deep-water sedimentary stratum quantitative model is high, and the result obtained when finally characterizing the deep-water sedimentary strata and improving the deep-water sedimentary model is relatively accurate and meets the use requirements. Therefore, the current deep-water sedimentary stratum quantitative model is retained at this time. This embodiment uses a rationality analysis method based on matching degree to screen deep-water sedimentary strata quantitative models, retains deep-water sedimentary strata quantitative models with a matching degree greater than or equal to a matching degree threshold, and eliminates deep-water sedimentary strata quantitative models with a matching degree less than the matching degree threshold, thereby ensuring a high-precision deep-water sedimentary strata quantitative model, and further ensuring the accuracy of the quantitative analysis of the deep-water sedimentary strata, that is, the accuracy of the results of the final characterization of the deep-water sedimentary strata and the improvement of the deep-water deposition model.

[0074] Step S44, quantitatively analyze the sedimentary characteristics of the deep-water sedimentary stratum quantitative model whose matching degree is greater than or equal to the matching degree threshold, and obtain the sedimentary characteristics quantitative analysis results. The sedimentary characteristics quantitative analysis results include sediment thickness, sand-to-formation ratio, single well virtual gamma curve, vertical lithofacies combination and planar sedimentary facies characteristics.

[0075] Step S45: Determine the deepwater sedimentation mode according to the quantitative analysis result of the sedimentation characteristics, wherein the deepwater sedimentation mode includes a submarine fan sedimentation mode dominated by gravity flow sedimentation and including deepwater suspended sedimentation.

[0076] In this embodiment, the rationality analysis of the quantitative model of deep-water sedimentary strata includes the following contents.

[0077] A rationality analysis was conducted on the deep-water sedimentary strata quantitative model obtained by coupling hydrodynamic equations with fuzzy logic rules. The rationality analysis required comparing the actual geological data such as well logging gamma curves, three-dimensional seismic profiles and lithofacies combinations in the target area with the single-well virtual gamma curves and sedimentary strata filling profiles of each sedimentary period output by the deep-water sedimentary strata quantitative model, and conducting an in-depth evaluation of the scientificity and accuracy of the deep-water sedimentary strata quantitative model to ensure that the matching degree of the final generated deep-water sedimentary strata quantitative model reached more than 80%.

[0078] In this embodiment, quantitative characterization of deep-water sedimentary characteristics includes the following contents.

[0079] The quantitative analysis of sedimentary characteristics of the deep-water sedimentary strata quantitative model in the target area was carried out to obtain sedimentary thickness, sand-to-stratigraphic ratio, vertical lithofacies combination, single-well virtual gamma curve, sedimentary filling characteristics of strata in each sedimentary period, and three-dimensional spatiotemporal distribution of various deep-water deposits, and the deep-water sedimentary pattern was described in detail. The sand-to-stratigraphic ratio is obtained by dividing the total volume of sandstone by the total volume of the stratum, the vertical lithofacies combination is obtained by the longitudinal section of the three-dimensional spatiotemporal distribution of the sedimentary body output by the deep-water sedimentary strata quantitative model, and the sedimentary facies characteristics are obtained by analyzing the sediment distribution of each layer output by the deep-water sedimentary strata quantitative model. Combining the above data analysis and processing, a submarine fan sedimentary model dominated by gravity flow deposition and containing deep-water suspended deposition is formed.

[0080] In actual application, the specific implementation process of the technical solution of this embodiment is as follows.

[0081] S1: Based on literature research and comprehensive analysis of geological data, analyze sedimentary characteristics and construct a regional geological conceptual model.

[0082] This embodiment systematically summarizes the research results of predecessors through literature research to form geological understanding; combines geological data such as seismic data, well logging data, core data and geochemical analysis test data to analyze and process the geological characteristics of the target area, characterize the characteristics of the sedimentary strata, and construct a regional geological concept model.

[0083] The induction and summary of previous research results were mainly achieved through literature research, including the research results of deep-water sediment types, reservoir distribution patterns, related sedimentary patterns, deep-water sedimentary characteristics and formation mechanisms in the target area, forming a preliminary geological understanding of the target area. These results mainly cover the source-sink system of deep-water sediments, transportation processes and hydrodynamic mechanisms, sedimentary structures and their causes, etc., providing theoretical support for the construction of regional geological conceptual models in the target area. These geological understandings were further verified and deepened in the subsequent analysis of seismic data, logging data, core and geochemical data in the target area.

[0084] Combined with various types of geological data, the target area is systematically analyzed: seismic data is used to divide the sequence stratigraphic framework of the target area, extract reflection characteristics to determine the sedimentary thickness and the spatial distribution of some sand bodies; well logging data is used to identify lithofacies and depict well-connected profiles through various logging curves to summarize the vertical lithofacies combination sequence and sedimentary facies distribution characteristics of the target area, clarify the vertical superposition relationship between sandstone and mudstone, and verify the sedimentary facies distribution characteristics obtained through literature research; core data and geochemical analysis test data are used to statistically analyze the grain size distribution, sediment components and grain size mean of sediments, depict the physical and chemical characteristics of deep-water sediments in the target area, and further deepen and improve the lithology combination, sedimentary facies and gravity flow fluid types in the target area. Based on the above data, the sedimentary facies characteristics are summarized and the sequence stratigraphic framework and sedimentary physicochemical properties are depicted to construct a regional geological conceptual model.

[0085] The geological data used in the construction process of the regional geological concept model include seismic data, logging data, core data and geochemical data, etc., and the geological understanding formed according to the literature survey and the regional geological background of the target area should be combined. The regional geological concept model specifically includes the basic geological parameters such as the stratigraphic framework, sand body distribution, sedimentary phase characteristics and typical lithofacies combination in the region. The regional geological concept model provides the necessary data support and theoretical basis for the next step of restoring key input parameters. However, due to the difficulties faced by deep-water sedimentary research such as scarcity and low quality of geological data, traditional research methods are mostly qualitative or semi-quantitative, and rely on a large amount of data support. Therefore, this embodiment reduces the dependence on geological data through forward simulation, and only a small amount of core data is required to complete the quantitative characterization of deep-water sedimentary strata. As an emerging direction of sedimentological research, forward simulation provides accurate and reliable technical support for deep-water sedimentary research at a lower cost and higher efficiency.

[0086] S2: Restore the key input parameters required for stratigraphic forward modeling based on the existing regional geological conceptual model and conduct parameter sensitivity analysis.

[0087] This embodiment extracts and restores the key input parameters required for sedimentary simulation under the guidance of the constructed regional geological conceptual model. Specifically, it includes: the scope of the simulation work area (determining the research scope based on the research purpose and the two-dimensional depth domain structural plane map of the target area), grid density (set in combination with the research scale, response speed and model resolution requirements), simulation time (set according to stratigraphic chronology information), initial paleo-geomorphology (using regional sedimentary phase characteristics, stratigraphic superposition relationships and three-dimensional seismic work area data to restore sedimentary paleo-geomorphology), sea level change curve (based on global sea level changes and superimposed high-frequency Milankovitch cycles), sediment accommodation space changes (combined with regional tectonic subsidence rate and sea level changes), sediment properties (derived from core grain size analysis and geochemical test data) and sediment provenance (determining the provenance direction and supply based on petrological analysis and the scope of ancient river basins).

[0088] These key input parameters are extracted and verified through the regional geological conceptual model, for example: the sediment supply is deduced based on the thickness and distribution of sediments, and the characteristics of the accommodative space variation are extracted by combining the stratigraphic distribution, paleo-geomorphology, sea level change and tectonic subsidence rate. The accuracy of the parameters directly determines the accuracy and applicability of the quantitative model of deep-water sedimentary formations in subsequent forward simulations. The more the simulation parameters fit the actual geological conditions of the work area, the more authentic and research-worthy the results of the quantitative model of deep-water sedimentary formations are.

[0089] S3: A quantitative model of deep-water sedimentary strata is established by coupling hydrodynamic equations with fuzzy logic rules.

[0090] This embodiment combines the restored key input parameters based on S2, couples the hydrodynamic equations with fuzzy logic rules, forms a method for coupling the hydrodynamic equations with fuzzy logic rules, and conducts sedimentary strata forward simulation to construct a quantitative model of deep-water sedimentary strata in the target area. The simulation process is as follows.

[0091] Hydrodynamic equation simulation process: The simulation equation is established based on the simplified Navier-Stokes hydrodynamic equation, and the above-recovered simulation parameters such as sea level change in the target area, sediment properties, hydrodynamic parameters and sediment supply rate are input. The equation is calculated by computer and the erosion, transportation and deposition process of sediments under hydrodynamic action is solved to obtain the quantitative model of deep-water sedimentary strata under hydrodynamic conditions. Parameters such as work area scope, grid density, accommodative space change, simulated initial paleo-geomorphology and simulation time are used to constrain the quantitative model of deep-water sedimentary strata and establish boundary conditions.

[0092] Fuzzy logic rule simulation process: Due to its special sedimentation mechanism, the pelagic-semi-pelagic suspended sediments are significantly different from other deep-water sediments, so the above hydrodynamic equations cannot be used for simulation and characterization. However, due to its ability to quantify qualitative geological theories, fuzzy logic rules can effectively characterize deep-water suspended sediments. Based on the data of the physical properties, sedimentation rate, formation process and development range of pelagic-semi-pelagic sediments, fuzzy sets and fuzzy rules are constructed using fuzzy logic rules. The development distribution range and sedimentation rate parameters of deep-water suspended sediments based on water depth are input, and fuzzy function equations are established. After computer solution and simulation, a quantitative model of deep-water sedimentary strata is obtained, and the three-dimensional spatiotemporal distribution of deep-water suspended sediments is output.

[0093] The method of coupling the hydrodynamic equation and the fuzzy logic rule in this embodiment is realized by the Sedfill3D sedimentary stratum forward simulation software, that is, the coupling of the hydrodynamic equation and the fuzzy logic rule is realized by the Sedfill3D sedimentary stratum forward simulation software, that is, a part of the key input parameters applicable to the hydrodynamic equation and another part of the key input parameters applicable to the fuzzy logic rule are simultaneously input into the Sedfill3D sedimentary stratum forward simulation software for calculation and simulation, so as to simulate and obtain a quantitative model of deep-water sedimentary strata. First, based on the different types of deep-water sediments (turbidity current sediments, isobathic current sediments, block transport sediments and pelagic-semi-pelagic sediments) and the dynamic mechanism of their sedimentary processes, the hydrodynamic equation is coupled with the fuzzy logic rule, and the turbidity current sediments, isobathic current sediments and block transport sediments adopt the hydrodynamic equation simulation method, and the pelagic-semi-pelagic sediments apply the fuzzy logic rule simulation method. On this basis, the key input parameters obtained by S2 are input, and the boundary conditions are set. Specifically, the hydrodynamic equation simulation method for turbidity current deposition, contour current deposition and mass transport deposition refers to inputting the simulation parameters required by the hydrodynamic equation, including the key input parameters of sea level change, sediment properties, hydrodynamic parameters and sediment supply rate reflecting turbidity current deposition, contour current deposition and mass transport deposition, into the Sedfill3D sedimentary stratigraphic forward simulation software. At the same time, the simulation parameters required by the fuzzy logic rule, including the key input parameters of deep-water suspended sediment development distribution range and sedimentation rate reflecting pelagic-semi-pelagic deposition, are also input into the Sedfill3D sedimentary stratigraphic forward simulation software. The initial paleo-geomorphology and simulation time parameters are constrained by boundary conditions, including simulation range, simulation time and simulation accuracy. Sedfill3D sedimentary stratum forward modeling software is used for calculation and simulation. The simulation function of Sedfill3D sedimentary stratum forward modeling software is used to generate a deep-water sediment stratigraphic quantitative model, and output a three-dimensional spatiotemporal distribution data body of deep-water sediments. The specific form of the three-dimensional spatiotemporal distribution data body is a unit square grid generated by the input work area range and grid density. Many unit square grids constitute the bottom surface of the deep-water sediment stratigraphic quantitative model, and the deposition thickness of different lithological sediments in each depositional period is displayed on each square grid.

[0094] The hydrodynamic equation simulation method is suitable for simulating the formation and evolution of sediment bodies with hydrodynamic transportation processes. It is often used to simulate turbidity current deposits, contour current deposits and mass transport deposits in deep-water sediments. However, it cannot effectively characterize deep-water suspended sediments composed of pelagic and semi-pelagic deposits, because deep-water suspended sediments have their own special transportation mechanism, usually showing the characteristics of slow vertical sedimentation in the water body, and do not have the process of being transported by hydrodynamic force.

[0095] Compared with the current forward simulation method, this embodiment adopts the method of coupling hydrodynamic equations and fuzzy logic rules to comprehensively consider the multiple sources and complex sedimentary processes of deep-water sediments, overcomes the problems of single model, imperfect sedimentary model and lack of strata, and the generated quantitative model of deep-water sedimentary strata is more realistic and has higher research value.

[0096] S4: Combine gamma-ray curves, seismic data, lithofacies associations and other actual geological data to conduct a rationality analysis of the quantitative model of deep-water sedimentary strata and quantitatively characterize the deep-water sedimentary pattern.

[0097] This embodiment uses well logging gamma curves, three-dimensional seismic exploration data in the target area, lithofacies combination sequences and other geological data to conduct rationality analysis on the deepwater sedimentary stratum quantitative model, eliminate the deepwater sedimentary stratum quantitative model with low matching degree, and finally obtain the deepwater sedimentary stratum quantitative model of the target area with high matching degree and accuracy. The quantitative analysis of sedimentary characteristics is carried out on the deepwater sedimentary stratum quantitative model of the target area to obtain sediment thickness, sand-to-ground ratio, lithofacies combination sequence, single well virtual gamma curve, sedimentary filling characteristics of different strata and three-dimensional spatiotemporal distribution of deepwater sediments. Through the above research results, the submarine fan sedimentation model dominated by gravity flow deposition and including deepwater suspended deposition is described in detail. In view of the lack of effective characterization of deepwater suspended deposition in previous studies, the deepwater sedimentation model is further improved.

[0098] A rationality analysis is conducted on the deepwater sedimentary formation quantitative model obtained in step S3. The rationality analysis requires comparing the actual logging gamma curve of the target area in step S1 with the single-well virtual gamma curve output in the simulated deepwater sedimentary formation quantitative model, and conducting an in-depth evaluation of the scientificity and accuracy of the deepwater sedimentary formation quantitative model to ensure that the final generated deepwater sedimentary formation quantitative model has high accuracy and authenticity.

[0099] Table 1 shows the comparison between the actual formation thickness and the simulated thickness of each control well. Figure 4 This is a comparison chart of the actual control well gamma curves of control well 2 and control well 3 and the single well virtual gamma curves. Figure 4 The horizontal axis is the GR value of the upper / lower strata of deep-water sediments, and the vertical axis is the depth value. Figure 4By comparing the actual GR value in the actual logging gamma curve and the simulated GR value in the single-well virtual gamma curve, it can be seen that the single-well virtual gamma curve corresponding to the deep-water sedimentary formation quantitative model has an accuracy of more than 80% compared with the actual logging gamma curve in the actual geological data, which means that the deep-water sedimentary formation quantitative model has high accuracy and certain practical geological significance. The deep-water sedimentary formation quantitative models with an accuracy of less than 80% are eliminated, and finally the deep-water sedimentary formation quantitative model of the target area with high matching and accuracy is obtained. The comparison process of the gamma curve is as follows: first, according to the actual control well coordinates, a virtual well is established in the deep-water sedimentary formation quantitative model, and the single well mud content data is extracted to generate a single well virtual gamma curve and compared with the actual control well gamma curve to compare the change and distribution of vertical sand and mudstone content in the entire well section of the single well. The gamma value of the gamma curve is related to the sandstone content and mudstone content. A high gamma value indicates a high mudstone content, and a low gamma value indicates a high sandstone content. The formula used to generate the gamma curve using the single well mud content data is as follows.

[0100] .

[0101] Among them, GR is the gamma value corresponding to the generated single well virtual gamma curve, is the output single well mud content, is the actual maximum gamma value of the control well, is the minimum gamma value of the actual control well.

[0102] Table 1 Comparison of actual formation thickness and simulated thickness of each control well

[0103]

[0104] In this embodiment, the rationality analysis of the deep-water sedimentary stratum quantitative model is helpful to improve the accuracy and authenticity of the deep-water sedimentary stratum quantitative model simulated in step S3. After the rationality is completed, the quantitative analysis of the sedimentary characteristics of the deep-water sedimentary stratum quantitative model is carried out. First, the sediment thickness of each sedimentary period is quantitatively characterized. The deep-water sedimentary stratum quantitative model can output the sediment volume per unit time step and unit grid. According to the time step corresponding to each sedimentary period and the range of the simulated target area, the sediment volume within the corresponding time step is divided by the corresponding simulation range to obtain the corresponding sediment thickness of each sedimentary period. The total sediment thickness of the target area is the sum of the sediment thickness of each sedimentary period. The sediment thickness calculation formula is as follows.

[0105] .

[0106] .

[0107] in, is the sediment thickness during a deposition period with t simulation time steps, t represents the tth simulation time step, is the sediment volume per unit grid, i represents the i-th unit grid, A is the simulation range of the target area, is the total deposition thickness.

[0108] In this embodiment, the quantitative model of deep-water sedimentary strata can also extract sediment volumes for different lithologies separately to clarify their spatial distribution. For example, the sediment volume is extracted and combined with the required unit grids to obtain the total volume of sandstone. The total volume of sandstone is compared with the total stratum volume to obtain the sand-to-formation ratio of the target area, which is used to characterize the distribution ratio of sandstone in the sedimentary strata. It reflects the spatial distribution characteristics of sandstone in the sedimentary environment, including the distribution range, connectivity and sandstone-enriched areas of sand bodies. Areas with high sand-to-formation ratios are often associated with high-quality reservoir distribution (with high porosity and high permeability), while areas with low sand-to-formation ratios may represent non-reservoir areas with poor reservoir potential.

[0109] This embodiment analyzes and processes the deep-water sedimentary three-dimensional spatiotemporal distribution data body output by the deep-water sedimentary stratum quantitative model, quantitatively characterizes the sedimentary characteristics, and can quantitatively analyze the sedimentary phases of different sedimentary periods on the plane, and can identify the sedimentary configurations such as submarine fan lobes, restricted waterways, weakly restricted waterways, non-restricted waterways, and pelagic-semi-pelagic sediments of multiple periods, and clarify the development and distribution range of different sedimentary phase belts in each sedimentary period, providing an effective basis for the positioning of high-quality reservoirs and reservoir connectivity analysis. In the vertical direction, the sedimentary characteristics such as lithological combinations, vertical distribution and reservoir connectivity formed in different sedimentary periods can be quantitatively analyzed to further deepen the sedimentary characteristics of the target area and improve the sedimentary model. At the same time, the three-dimensional spatiotemporal distribution data body of deep-water deposits of different lithologies can be extracted based on the sediment particle size, and the spatial distribution and evolution formation process of oil and gas reservoir systems such as sandstone reservoirs, muddy source rocks, and mudstone caprocks can be quantitatively characterized. For the sedimentary process of deep-water sediments, the three-dimensional spatiotemporal distribution of deep-water sediments output by the deep-water sedimentary strata quantitative model can also be effectively simulated and displayed. The total three-dimensional spatiotemporal distribution data volume is separated according to the time step, and the sea level change curve is superimposed. After processing using simulation software, a simulation display animation of the deep-water sedimentary deposition process can be obtained.

[0110] The specific implementation scheme of the embodiment will be described in detail below in conjunction with a specific embodiment, taking a passive continental margin basin as the research background.

[0111] The method for quantitative characterization of deep-water sediments based on sedimentary stratum forward modeling provided in this embodiment includes the following steps.

[0112] (1) Based on literature research and comprehensive analysis of geological data, the sedimentary characteristics are analyzed and a regional geological conceptual model is constructed.

[0113] This embodiment uses the Upper Cretaceous strata of a passive continental margin basin as a research example. The structural settlement of this area was stable during the Late Cretaceous sedimentary period, and no obvious tectonic activity occurred; the sedimentary environment was marine, and it was a typical passive continental margin basin; in the Late Cretaceous, the basin continuously received sediment input from the delta at the edge of the continental shelf, and developed multiple periods of deep-water submarine fans, and the stratigraphic deposition was relatively continuous. The reservoir is deep-water turbidite, and the source rock is a large set of mud shales developed in the early Late Cretaceous. The pelagic-semi-pelagic sediments act as an effective cap rock. Based on a large amount of literature research, analysis of geological data, and inductive geological knowledge, a regional geological conceptual model of the target area is established.

[0114] (2) Restore the key input parameters required for stratigraphic forward modeling based on the existing regional geological conceptual model and conduct parameter sensitivity analysis.

[0115] Under the guidance of the regional geological concept model, this embodiment sets the simulation time to 35 Myr, the display time interval to 100 kyr, the fluid calculation time interval to 25 kyr, and the model outputs a total of 350 layers; the number of grids is set to 93 horizontally and 100 vertically, the grid spacing is 5 km, and the total simulation range is 460 km horizontally and 495 km vertically, a total of 227,700 square kilometers. The initial paleogeography of the sedimentary simulation is restored by the two-dimensional seismic depth domain structural profile and sedimentary phase model map, which can be divided into the onshore part, continental shelf, continental slope, continental rise and part of the deep sea plain from shallow to deep. The regional tectonic settlement is jointly constrained by geological data such as the single well structural settlement, the typical settlement rate model of the passive continental margin basin, and the decompaction correction of the sedimentary strata. The sediment property parameter settings are shown in Table 2, taking into account the core analysis data and sedimentary stratum grain size statistics of the region, and referring to the typical submarine fan sediment grain size distribution. The sediment source parameter settings are shown in Table 3. They are set based on the hydrodynamic conditions and typical fluid dynamic parameters of the target area, and refer to the development location of the Late Cretaceous ancient river basin and continental shelf delta in the target area. The pelagic-hemipelagic sediment parameters refer to the global average background sedimentation rate (<10 cm / kyr) and the typical development distribution range, and are set in combination with the geological data of the target area, such as Figure 2 and Figure 3 The above are the main parameters of the key input parameters required for simulation. After the other key input parameters are set, sensitivity analysis is carried out on the parameters, and positive feedback correction is performed on the parameters according to the results of each analysis. The parameters are iterated continuously until the matching degree between the parameter settings and the real stratigraphic pattern of the target area is increased to within a reasonable error range, ensuring the authenticity of the quantitative model of deep-water sedimentary stratigraphy obtained by subsequent simulation.

[0116] Table 2 Sediment property parameters

[0117]

[0118] Table 3 Sediment source parameter settings

[0119]

[0120] (3) Deepwater sedimentary forward simulation is carried out by coupling hydrodynamic equations with fuzzy logic rules to establish a quantitative model of deepwater sedimentary strata.

[0121] This embodiment takes the deep-water turbidite fan deposition system as an example. The turbidite sandstone includes coarse-medium sandstone, fine-very fine sandstone and very fine-siltstone, which are distributed vertically overlapping with mudstone. The traditional hydrodynamic equation simulation method can effectively characterize the formation process of turbidite sandstone, that is, the terrigenous clastic sediments are transported to the deep-water basin by gravity flow and deposited, but the formed mudstone not only has the contribution of fine-grained terrigenous clastic sediments, but also the contribution of deep-water suspended sediments. Using only the hydrodynamic equation simulation method, it is impossible to effectively characterize this part of mudstone with inconsistent genetic processes, resulting in missing strata and incomplete characterization of the deep-water turbidite fan deposition pattern. The fuzzy logic rule simulation method can effectively characterize the formation process of the missing mudstone. Therefore, this embodiment combines the hydrodynamic equation simulation method and the fuzzy logic rule simulation method, and adopts the method of coupling hydrodynamic equations and fuzzy logic rules to effectively characterize deep-water deposition systems such as deep-water turbidite fans.

[0122] In this embodiment, the simulation parameters required by the hydrodynamic equation (including key input parameters of sea level changes, sediment properties, hydrodynamic parameters and sediment supply rate reflecting turbidity current deposition, contour current deposition and mass transport deposition) are input into the Sedfill3D sedimentary stratum forward modeling software. At the same time, the simulation parameters required by the fuzzy logic rule (including key input parameters of deep-water suspended sediment development distribution range and sedimentation rate reflecting pelagic and semi-pelagic deposition) are also input into the Sedfill3D sedimentary stratum forward modeling software. The boundary conditions are set by using parameters such as work area scope, grid density, accommodative space variation, simulated initial paleo-geomorphology and simulation time to constrain, including simulation scope, simulation time and simulation accuracy. The Sedfill3D sedimentary stratum forward modeling software is used for calculation and simulation, and the simulation function of the Sedfill3D sedimentary stratum forward modeling software is used to generate a quantitative model of deep-water sedimentary strata.

[0123] This embodiment uses the deep-water turbidite fan sedimentary system of the passive continental margin basin in the South Atlantic as a research example. The key input parameters corresponding to the hydrodynamic equation include the properties of terrigenous clastic sediments, material source input parameters, slope landslide slope parameters, and fluid sampling interval parameters; the key input parameters corresponding to the fuzzy logic rule include sedimentation velocity and distribution range, and the sea level change, tectonic settlement, initial sedimentary bottom shape, simulation time and simulation grid together constitute the boundary conditions. Among them, the key input parameters corresponding to the hydrodynamic equation are set as follows: The sediment property parameters of terrigenous clastics are set as shown in Table 2. Based on core observation and microscopic feature analysis, grain size statistics and literature research, the sediment property parameters required for the simulation are restored, including lithology, average grain size and density. For example, the properties of terrigenous clastic sediments mainly include coarse sand, medium sand, fine sand and mud. The average particle sizes of coarse sand, medium sand, fine sand and mud are 601.0 μm, 307.0 μm, 172.0 μm and 3.5 μm respectively, and the densities of coarse sand, medium sand, fine sand and mud are 2650.00 kg / m 3 、2600.00kg / m 3 、2600.00kg / m 3 、2550.00kg / m 3 . The setting of the source input parameters is based on the literature survey of the study area, source-sink system analysis, ancient river basin range, modern observations of typical gravity flow formation, and the principle of conservation of matter. The sediment source parameter setting table is shown in Table 3. This embodiment sets sources No. 1, 2, 3, and 4, and the simulation time is set to 35 Myr. The flow rate, concentration, and proportion of coarse sand, medium sand, fine sand, and mud in each source are shown in Table 3. The setting of the slope landslide slope parameter refers to the typical flume test results and the formation inclination of the study area, and the fluid sampling interval is set by comprehensively considering the simulation speed and the response degree of the results. The key input parameters corresponding to the fuzzy logic rules are set as follows: The sedimentation velocity and distribution range in the fuzzy logic rules are clarified through literature surveys and ocean drilling well data analysis to clarify the sedimentation rate and sedimentation range of deep-water suspended sediments, such as Figure 2 and Figure 3As shown, in this embodiment, when the sedimentation velocity is 0.00004 meters / year, the corresponding deep-water suspended sedimentation is about 0.4; when the sedimentation velocity is 0.00008 meters / year, the corresponding deep-water suspended sedimentation is about 1. When the depth reaches 3000 meters, the deep-water suspended sedimentation is about 1. Among them, the sedimentation amounts of 0.4 and 1 refer to the sedimentation proportions set in the fuzzy logic rules, and the values ​​are 0~1. The boundary condition parameters are set as follows: the sea level changes in the boundary condition parameters are based on the global sea level changes and superimposed on the Milankovitch cycle to form a high-frequency (five-level) sea level change curve; the initial sedimentary bottom shape is constructed by interpreting the top and bottom interfaces of different sedimentary periods through geological data, and is set based on this; the tectonic settlement refers to the tectonic settlement of multiple single wells in the study area, and is set in combination with the settlement trend of the typical passive continental margin basin; the simulation time is based on the formation and end time of the target layer segment studied, and the simulation grid is set according to the scope of the study area.

[0124] After analyzing the rationality of key input parameters, this embodiment uses a method of coupling hydrodynamic equations and fuzzy logic rules to perform forward simulation of deep-water sedimentation and establish a quantitative model of deep-water sedimentary formations. The process of the method of coupling hydrodynamic equations and fuzzy logic rules is as follows: Figure 5 As shown, it includes four parts: deep-water sedimentation model, simulation method, equation calculation and solution, and simulation results. Among them, the deep-water sedimentation model mainly includes turbidity current deposition, contour current deposition, block transport body and ocean-semi-ocean deposition, and the simulation method is a method of coupling hydrodynamic equations and fuzzy logic rules. The method of coupling hydrodynamic equations and fuzzy logic rules is an algorithm composed of the coupling of hydrodynamic equations and fuzzy logic rules, and is matched with a sedimentation dynamics mechanism. The hydrodynamic equation is associated with turbidity current deposition, contour current deposition, and block transport body, while the fuzzy logic rule is associated with ocean-semi-ocean deposition. The key input parameters of the simulation are input into the Sedfill3D sedimentary stratum forward simulation software, and the simulation results are obtained by solving and simulating the Sedfill3D sedimentary stratum forward simulation software, that is, a quantitative model of deep-water sedimentary strata is established.

[0125] This embodiment is guided by the sediment types and their deposition processes and mechanisms in a deepwater environment, and the key input parameters restored by the regional geological conceptual model are input into the Sedfill3D sedimentary strata forward simulation software. The equation is solved and simulated by the Sedfill3D sedimentary forward simulation software to obtain a quantitative model of deepwater sedimentary strata. Forward simulation of deepwater sedimentary strata usually only uses hydrodynamic equations for simulation, and the research objects are mostly submarine fan systems. However, the characterization of the obtained quantitative model of deepwater sedimentary strata is not perfect, and the deepwater sedimentary strata quantitative model lacks pelagic-semi-pelagic sedimentary strata, so the stratum thickness and vertical lithofacies combination will be affected to varying degrees. The technical solution of this embodiment has improved the deepwater sedimentary model to a certain extent, and improved the rationality and authenticity of the quantitative model of deepwater sedimentary strata.

[0126] (4) Combine gamma-ray curves, seismic data, lithofacies associations and other data to conduct a rational analysis of the quantitative model of deep-water sedimentary strata and quantitatively characterize the deep-water sedimentary pattern.

[0127] This embodiment performs a rationality analysis on the established deep-water sedimentary stratum quantitative model, and obtains a reasonable deep-water sedimentary stratum quantitative model after correction according to the actual geological data of the region. By conducting data analysis on the obtained deep-water sedimentary stratum quantitative model, the single-well virtual gamma curve output by the deep-water sedimentary stratum quantitative model is compared with the natural gamma curve, and the degree of agreement reaches 90%, which meets the standard of model rationality analysis, is closest to the actual geological conditions, and has high authenticity. Quantitative research on the deep-water sedimentary stratum quantitative model can obtain a sediment thickness map and a sand-to-ground ratio superposition map, and quantitative research can be carried out on each sedimentary period to explore the migration process of the sedimentary center and the development pattern of the submarine fan. The sand-to-ground ratio superposition map of the entire sedimentary period superimposes the ratio of the total volume of sandstone to the total volume of the stratum in the three sedimentary periods, and can quantitatively study the distribution range of sandstone and the distribution characteristics of the sedimentary configuration. Compared with the actual geological data, it has a high degree of agreement, which provides a basis for deep-water oil and gas exploration and development. Research and analysis were conducted on the vertical stratigraphic lithology combination. In the vertical direction, turbidite channels formed by multiple periods of submarine fans are sandwiched in the strata with pelagic and semi-pelagic sediments as the background. Sedimentary configurations such as multiple periods of submarine fan lobes, restricted channels, weakly restricted channels, unrestricted channels, and pelagic and semi-pelagic sediments can be identified. This improves the submarine fan sedimentary model dominated by turbidite deposits and containing deep-water suspended deposits, and provides data support for the distribution characteristics of high-quality reservoirs and the prediction of oil and gas enrichment areas.

[0128] This embodiment provides a method for quantitative characterization of deep-water sediments based on stratigraphic forward modeling. On the basis of literature research and analysis of actual geological data, it comprehensively analyzes the regional geological profile of the target area, summarizes the sedimentary characteristics, and establishes a regional geological conceptual model. Based on the established regional geological conceptual model, the key input parameters required for the simulation are restored, including the initial paleo-geomorphology of deposition, sea level changes, and provenance properties. The rationality of the deep-water sedimentary stratum quantitative model is analyzed in combination with geological data to verify the rationality of the deep-water sedimentary stratum quantitative model. A quantitative analysis is performed on the high-precision deep-water sedimentary stratum quantitative model to clarify the deep-water sedimentary characteristics and three-dimensional spatiotemporal distribution, and to improve the deep-water sedimentary model.

[0129] This embodiment adopts the method of coupling hydrodynamic equations and fuzzy logic rules to carry out the quantitative model of deep-water sedimentary strata established by sedimentary forward simulation, which is more in line with actual geological conditions and has stronger authenticity. This embodiment quantitatively characterizes the deep-water sedimentary strata of the Late Cretaceous in a passive continental margin basin, analyzes the planar sedimentary phase characteristics, characterizes the vertical lithology combination, and calculates the sediment thickness map and sand-to-ground ratio superposition map of different sedimentary periods. At the same time, the role of multiple sedimentary processes in deep-water environments has also been characterized, and the obtained quantitative model of deep-water sedimentary strata is more meaningful for research, which provides strong support for the characterization of deep-water sedimentary patterns, the characterization of sedimentary reservoirs, and the development of research on oil and gas enrichment laws.

[0130] This embodiment takes into account that the hydrodynamic equation and diffusion equation algorithm can effectively and quantitatively simulate the submarine fan source-sink system, but it cannot simulate the deep-sea-semi-pelagic deep-water suspended sedimentation, and thus cannot effectively characterize the integrity of deep-water sedimentation. The application of fuzzy logic rule algorithm can establish an algorithm based on modern deep-sea sedimentary observations to make up for the deep-sea-semi-pelagic deep-water sedimentation, and effectively solve the problem of missing strata that only relies on sedimentary dynamic equations or diffusion equations for simulation. In view of the fact that the current stratum forward modeling method cannot simulate the deep-water suspended sedimentation process, this embodiment proposes a stratum forward modeling method based on the method of coupling hydrodynamic equations and fuzzy logic rules, which can be used to quantitatively characterize deep-water sedimentary strata and improve deep-water sedimentary patterns. The method includes establishing a regional geological concept model based on literature research and comprehensive analysis of geological data; and determining the key input parameters required for simulation based on the established regional geological concept model and geological geophysical data; simulating and establishing a deep-water sedimentary stratum quantitative model by coupling hydrodynamic equations and fuzzy logic rules; by calibrating and verifying the deep-water sedimentary stratum quantitative model, the deep-water sedimentary strata can be quantitatively characterized and the deep-water sedimentary pattern can be improved. This method was applied to carry out forward modeling of deep-water deposition. The results showed that the stratigraphic forward modeling of deep-water deposition based on the method of coupling hydrodynamic equations and fuzzy logic rules can effectively simulate the deep-water deposition process and quantitatively characterize the deep-water deposition pattern.

[0131] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0132] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A method for quantitative characterization of deep-water sediments based on stratigraphic forward modeling, characterized in that: The deep-water sediment quantitative characterization method based on stratigraphic forward modeling includes: Obtain geological data of the target area, analyze sedimentary characteristics based on the geological data, and construct a regional geological conceptual model; Determine the key input parameters required for stratigraphic forward modeling based on the regional geological conceptual model; the key input parameters include initial sedimentary paleo-geomorphology, changes in sediment accommodation space, sea level changes, sediment properties and sediment provenance parameters; According to the key input parameters, a method of coupling hydrodynamic equations and fuzzy logic rules is used to perform forward simulation of deep-water sedimentary strata, and establish a quantitative model of deep-water sedimentary strata; the method of coupling hydrodynamic equations and fuzzy logic rules refers to an algorithm for simulating and establishing the quantitative model of deep-water sedimentary strata obtained by coupling hydrodynamic equations and fuzzy logic rules according to the source, sedimentation process and sediment type of deep-water sediments; the quantitative model of deep-water sedimentary strata includes spatial distribution information and accommodative spatial variation information of sediments of different particle sizes within the simulation time; The rationality of the deep-water sedimentary stratum quantitative model is analyzed to quantitatively characterize the deep-water sedimentary stratum and improve the deep-water sedimentary model.

2. The method for quantitative characterization of deep-water sediments based on stratigraphic forward modeling according to claim 1, characterized in that: Obtain geological data of the target area, analyze sedimentary characteristics based on the geological data, and construct a regional geological conceptual model, including: Determine the previous geological research results of the target area through literature research and form a basic geological understanding of the target area; Acquire the geological data of the target area; the geological data include seismic data, well logging data, core data, field outcrop data and geochemical analysis and test data of the target area; Based on the geological data and basic geological knowledge of the target area, the geological characteristics of the target area are analyzed, the characteristics of the sedimentary strata are characterized, and a regional geological conceptual model is established.

3. The method for quantitative characterization of deep-water sediments based on stratigraphic forward modeling according to claim 2, characterized in that: According to the regional geological conceptual model, the key input parameters required for stratigraphic forward modeling are determined, including: According to the regional geological conceptual model, the geological data and the basic geological knowledge of the target area, the key input parameters required for stratigraphic forward modeling are restored to obtain the key input parameters.

4. The method for quantitative characterization of deep-water sediments based on stratigraphic forward modeling according to claim 1, characterized in that: After the step of determining key input parameters required for stratigraphic forward modeling according to the regional geological conceptual model, the deepwater sediment quantitative characterization method based on stratigraphic forward modeling further includes: A parameter sensitivity analysis is performed on the key input parameters to obtain the key input parameters after the parameter sensitivity analysis; the key input parameters after the parameter sensitivity analysis are used as the key input parameters, and a method of coupling hydrodynamic equations and fuzzy logic rules is used to perform forward simulation of deep-water sedimentary formations, so as to establish a quantitative model of the deep-water sedimentary formations.

5. The method for quantitative characterization of deep-water sediments based on stratigraphic forward modeling according to claim 1, characterized in that: According to the key input parameters, the forward simulation of deep-water sedimentary formations is carried out by coupling the hydrodynamic equations with fuzzy logic rules to establish a quantitative model of deep-water sedimentary formations, which specifically includes: Based on the method of coupling hydrodynamic equations and fuzzy logic rules, the key input parameters are input into Sedfill3D sedimentary stratum forward modeling software, and solved and simulated by Sedfill3D sedimentary stratum forward modeling software to obtain the quantitative model of deep-water sedimentary strata.

6. The method for quantitative characterization of deep-water sediments based on stratigraphic forward modeling according to claim 1, characterized in that: The rationality of the deepwater sedimentary stratum quantitative model is analyzed, the deepwater sedimentary stratum is quantitatively characterized, and the deepwater sedimentary model is improved, including: Determine rationality analysis data of the target area based on the geological data, wherein the rationality analysis data includes well logging gamma curve data, three-dimensional seismic profile data, and lithofacies combination sequence data; Comparing the rationality analysis data with the single well virtual gamma curve and the sedimentary stratum filling profiles of each sedimentary period output by the deep-water sedimentary stratum quantitative model to determine the matching degree of the deep-water sedimentary stratum quantitative model; Determining a rationality analysis result of the matching degree of the deep-water sedimentary stratum quantitative model according to the matching degree and matching degree threshold of the deep-water sedimentary stratum quantitative model; Performing a quantitative analysis of sedimentary characteristics on the deep-water sedimentary stratum quantitative model whose matching degree is greater than or equal to the matching degree threshold, and obtaining a quantitative analysis result of sedimentary characteristics; the quantitative analysis result of sedimentary characteristics includes sedimentary thickness, sand-to-formation ratio, single-well virtual gamma curve, vertical lithofacies combination and planar sedimentary facies characteristics; The deepwater sedimentation pattern is determined based on the quantitative analysis results of the sedimentary characteristics; the deepwater sedimentation pattern includes a submarine fan sedimentation pattern dominated by gravity flow deposition and containing deepwater suspended deposition.

7. The method for quantitative characterization of deep-water sediments based on stratigraphic forward modeling according to claim 6, characterized in that: The single-well virtual gamma curve is a gamma curve generated by applying the single-well shale content data, and the calculation formula used is: ； Among them, GR is the gamma value corresponding to the generated single well virtual gamma curve, is the output single well mud content, is the actual maximum gamma value of the control well, is the minimum gamma value of the actual control well.

8. The method for quantitative characterization of deep-water sediments based on stratigraphic forward modeling according to claim 6, characterized in that: The deposition thickness was calculated using the following formula: ； ； in, is the sediment thickness during a deposition period with t simulation time steps, t represents the tth simulation time step, is the sediment volume per unit grid, i represents the i-th unit grid, A is the simulation range of the target area, is the total deposition thickness.

9. The method for quantitative characterization of deep-water sediments based on stratigraphic forward modeling according to claim 6, characterized in that: The matching degree threshold is 80%.

10. A deepwater sediment quantitative characterization system based on stratigraphic forward modeling, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method for quantitative characterization of deep-water sediments based on stratigraphic forward modeling as described in any one of claims 1 to 9.

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