A reservoir wettability prediction method based on cross-scale data fusion

Abstract

This invention belongs to the field of oil and gas field exploration and development technology, and specifically relates to a reservoir wettability prediction method based on cross-scale data fusion. It includes the following steps: S1: Acquiring and preprocessing various logging data; S2: Identifying target mineral types and determining elemental substitution relationships; S3: Calibrating the wettability of mineral samples from the well; S4: Establishing a molecular dynamics simulation system for the studied minerals; S5: Setting molecular dynamics simulation parameters and performing calculations; S6: Analyzing wettability parameters under different substitution ratios; S7: Establishing Fe... 2+ The quantitative relationship between substitution ratio and wettability; S8: Establish wettability grading standards and output evaluation results. This invention relies on well logging data to achieve continuous calculations at the well section scale, which can form a continuous profile of wettability changes with depth. It can be extended to other elements, mineral types and fluid systems, and even simulate the temperature and pressure corresponding to actual formation depths, thus having a wide range of applications.

Description

Technical Field

[0001] This invention relates to the field of oil and gas field exploration and development technology, specifically to a reservoir wettability prediction method based on cross-scale data fusion. Background Technology

[0002] Reservoir wettability is a crucial parameter affecting oil-water distribution, capillary force, displacement efficiency, and ultimate recovery rate, playing a vital role in reservoir evaluation, development scheme design, and enhanced oil recovery. Existing wettability evaluation methods mainly include the contact angle method, nuclear magnetic resonance (NMR) method, and self-absorption method. While these methods can experimentally reflect the wettability characteristics of rock surfaces, they still have the following limitations:

[0003] It is highly dependent on core samples, and sampling is difficult, making it hard to achieve continuous evaluation of wettability across the entire well section and all formations;

[0004] Wettability testing is costly, time-consuming, and some methods are destructive.

[0005] The results are mostly local or discrete point information, which is difficult to characterize the continuous wettability distribution of the reservoir with depth.

[0006] Traditional wettability interpretation methods based on well logging data are mostly based on empirical judgment or indirect inference, lacking a quantitative relationship between changes in mineral microstructure and wettability;

[0007] For complex reservoirs such as carbonate rocks, there are often ion substitution, impurity incorporation and changes in surface electrical properties within the minerals. These microscopic factors can alter the hydration layer structure and fluid adsorption behavior on the mineral surface, thereby affecting wettability, but existing methods are difficult to accurately reflect these factors.

[0008] Taking calcite as an example, the Ca in the calcite lattice 2+ Fe 2+ Plasma substitution alters the surface chemical composition, surface electrical properties, and interactions with water molecules of minerals, leading to changes in wettability. However, current technologies lack a method to quantitatively correlate elemental logging curves, the degree of mineral ion substitution, and wettability. Therefore, it is necessary to propose a new evaluation method to achieve continuous, quantitative, and interpretable assessment of reservoir wettability. Summary of the Invention

[0009] The purpose of this section is to outline some aspects of the embodiments of the present invention and to briefly describe some preferred embodiments. Simplifications or omissions may be made in this section, as well as in the abstract and title of this application, to avoid obscuring the purpose of these documents; however, such simplifications or omissions should not be construed as limiting the scope of the invention.

[0010] To address the aforementioned technical problems, according to one aspect of the present invention, the present invention provides the following technical solution:

[0011] A reservoir wettability prediction method based on cross-scale data fusion includes the following steps:

[0012] S1: Collect and preprocess various logging data: determine the main reservoir mineral types and determine whether the changes in element content mainly come from ion substitution within the target mineral;

[0013] S2: Identify target mineral types and determine elemental substitution relationships: perform mineral inversion to obtain a continuous mineral content profile;

[0014] S3: Wetness calibration of mineral samples in wells: Screen the depth positions of elemental logging curves, obtain core samples, and perform wettability tests on the samples;

[0015] S4: Establish a molecular dynamics simulation system for studying minerals: establish mineral models and liquid models, and combine mineral models with different degrees of element substitution with the same solution model respectively;

[0016] S5: Set molecular dynamics simulation parameters and perform calculations;

[0017] S6: Analysis of wettability parameters under different substitution ratios: The water film method was used to analyze different Fe... 2+ Changes in the wettability of calcite surface at different substitution ratios;

[0018] S7: Establish Fe 2+ Quantitative relationship between substitution ratio and wettability: based on different Fe 2+ A molecular dynamics model of the mineral-fluid interface was constructed under the substitution ratio. The mean square displacement curves of the interface molecules were extracted and fitted to obtain the diffusion coefficient. The peak values ​​of strong adsorption peaks in the relative concentration distribution of interface molecules were extracted. Combined with the corresponding Fe... 2+ Based on the simulation results under the substitution ratio, a quantitative relationship model is established;

[0019] S8: Establish wettability grading standards and output evaluation results: Obtain Fe based on mineral composition analysis results and elemental test results. 2+ Substitution ratio Substituting these values ​​into the quantitative relationship model yields a comprehensive wettability evaluation index.

[0020] As a preferred embodiment of the reservoir wettability prediction method based on cross-scale data fusion described in this invention, in step S1, the collected logging data are elemental logging data, including at least: Ca element curves and Fe element curves; depending on the specific reservoir conditions, they also include Mg, Si, Al, K, Na, P, Ti, and Mn element curves; conventional logging data: including natural gamma ray, sonic transit time, density, neutron porosity, and resistivity; core observation data: including lithology, color, fractures, pores, and infill development; thin section identification data: including mineral composition, particle structure, cementation type, and pore type; X-ray diffraction analysis data, i.e., XRD mineral composition analysis results; formation water salinity, ionic composition, temperature, pressure fluid, and reservoir conditions;

[0021] The preprocessing specifically includes data filtering, depth correction, outlier removal, and curve unit unification. Through preprocessing operations, the target layer data is highlighted, and different curves have a unified depth benchmark and comparability.

[0022] As a preferred embodiment of the reservoir wettability prediction method based on cross-scale data fusion described in this invention, the specific method of S2 is as follows: For the target depth point Z, the Fe element of the target layer first needs to be corrected. Using XRD analysis and mineral inversion results, the Fe element corresponding to other iron-bearing minerals is proportionally subtracted, and the same applies to Ca element. Subsequently, for the target mineral calcite, the Fe is calculated based on the Ca and Fe element contents. 2+ Relative to Ca 2+ The substitution ratio of the sites is expressed in the following form:

[0023] (2-1)

[0024] in, Indicates depth Fe 2+ For Ca 2+ The relative substitution ratio of sites, This indicates the molar content of Fe at that depth. This indicates the molar content of Ca at that depth.

[0025] As a preferred embodiment of the reservoir wettability prediction method based on cross-scale data fusion described in this invention, the specific method of S3 is as follows: First, based on elemental logging data, XRD mineral composition analysis results, and core observation results, a target depth point Z is selected; a core sample is obtained at this depth, and the sample surface is cut, polished, and cleaned; after sample processing, a contact angle experiment is conducted on the sample surface under set temperature and pressure conditions to determine the contact angle of the aqueous phase on the sample surface. The specific calibration process requires multiple tests, each time selecting different surfaces of the sample to measure the wetting angle, and taking the average value as the final wetting angle result. Among these, the contact angle... This is used to characterize the actual wettability of mineral samples at this depth; simultaneously, using the elemental logging results corresponding to this depth point Z, the elemental substitution ratio in the target mineral at this depth is calculated using Equation 2-1; thus, the elemental substitution ratio at a certain depth in the well is determined. Compared with the measured contact angle Establish corresponding relationships.

[0026] As a preferred embodiment of the reservoir wettability prediction method based on cross-scale data fusion described in this invention, the method for constructing the mineral model in S4 is as follows: a calcite cell model is established based on the calcite crystal structure parameters; calcite cells are imported from the crystal database and experimental cell parameters; after importing the cells, the original calcite cells need to be geometrically optimized to achieve an energy-stable state; then, a calcite surface model is formed by cutting along a specific crystal plane; and finally, a vacuum layer is added to the established mineral surface.

[0027] As a preferred embodiment of the reservoir wettability prediction method based on cross-scale data fusion described in this invention, the specific method of step S6 is as follows: using raw calcium calcite and 100% Fe... 2+ Taking the replaced calcite as an example, firstly, the relative concentration distribution of solution molecules in the vertical direction after the system stabilizes is statistically analyzed. Using the calcite surface as a reference zero point, the number distribution of solution molecules within different distance intervals is obtained. Then, the number of solution molecules within each distance interval is converted into relative concentration or number density, forming a relative concentration distribution curve of solution molecules, thus determining the adsorption region and its boundary position on the calcite surface. After obtaining the spatial distribution characteristics of water molecules, mean square displacement analysis is further performed on the interfacial water molecules to calculate the relative concentration distribution of different Fe atoms. 2+ The diffusion coefficient of water molecules under the substitution ratio condition is calculated based on the mean square displacement (MSD) curve over the simulation time using molecular dynamics trajectories. Its expression is:

[0028] (6-1)

[0029] in for The displacement vector of water molecules at time . The position vector at the initial moment. This indicates an overall average over multiple molecules and multiple time points;

[0030] Calculate the corresponding diffusion coefficient based on the slope of the MSD curve. Its expression is:

[0031] (6-2)

[0032] in For the diffusion dimension.

[0033] As a preferred embodiment of the reservoir wettability prediction method based on cross-scale data fusion described in this invention, the specific method of step S7 is as follows:

[0034] (7-1)

[0035] (7-2)

[0036] in, For Fe 2+ The substitution ratio of the target cation in the mineral lattice, The diffusion coefficient of water molecules at the interface. The peak value of the strong adsorption peak in the relative concentration distribution curve of water molecules at the interface;

[0037] The specific formula for fitting calculation is as follows:

[0038] (7-3)

[0039] (7-4)

[0040] A comprehensive wettability evaluation index is established, combining the above diffusion coefficient with the peak value of strong adsorption, for quantitative characterization of different Fe... 2+ The changes in wettability of reservoir mineral surfaces under different substitution ratios are evaluated by a comprehensive wettability assessment index determined jointly by the diffusion coefficient and the peak value of the strong adsorption peak.

[0041] (7-5)

[0042] in As a comprehensive wettability evaluation index, and These represent the peak value and diffusion coefficient of the benchmark strong adsorption peak of the calibration mineral, respectively. and The weighting coefficients are used to characterize the contribution of the strong adsorption peak value and the interfacial water molecule diffusion coefficient to the comprehensive wettability evaluation index.

[0043] As a preferred embodiment of the reservoir wettability prediction method based on cross-scale data fusion described in this invention, the specific method of step S8 is as follows:

[0044] (8-1)

[0045] (8-2)

[0046] (8-3)

[0047] in, For the target well depth The corresponding interfacial water molecule diffusion coefficient, For the target well depth The corresponding strong adsorption peak value. For the target well depth The comprehensive wettability evaluation index at the location; thus forming the Fe content of the target well section varying with depth. 2+ Substitution ratio curve, diffusion coefficient curve, strong adsorption peak value curve, and comprehensive wettability evaluation curve enable continuous evaluation of reservoir wettability.

[0048] Based on the measured wettability results of typical reservoir samples, a comprehensive wettability evaluation index was established for S6. The reservoir wettability classification standard is established based on the calibration, and the continuous wettability evaluation results and wettability grade distribution of the target well section are output.

[0049] Compared with existing technologies, the advantages of this invention are as follows: This invention connects microscopic mechanisms with macroscopic logging data. It establishes a quantitative relationship between elemental substitution ratios and wettability through molecular dynamics simulations, enabling the explanation of wettability changes caused by variations in mineral composition at the microscopic level. Furthermore, the method is based on molecular dynamics and mineral crystal chemistry, therefore the output results are not purely empirical fitting but have clear microscopic physical meaning. This invention can achieve continuous calculations at the well section scale using logging data even in the absence of complete core data, forming a continuous profile of wettability changes with depth. It can provide direct support for development decisions; the wettability evaluation results can be used to guide water injection development, oil displacement system selection, acid fracturing design, and enhanced oil recovery scheme formulation. This invention is not only applicable to Fe... 2+ Alternative Ca 2+ The calcite system can also be extended to other elements, mineral types and fluid systems, and even simulate the temperature and pressure corresponding to actual strata at actual depths, making it widely applicable. Attached Figure Description

[0050] To more clearly illustrate the technical solutions of the embodiments of the present invention, the present invention will be described in detail below with reference to the accompanying drawings and detailed embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. Wherein:

[0051] Figure 1 shows the contact angle test diagram of a reservoir wettability prediction method based on cross-scale data fusion according to the present invention.

[0052] Figure 2 shows the contact angle test results of a reservoir wettability prediction method based on cross-scale data fusion according to the present invention.

[0053] Figure 3 shows the calcite lattice model of the reservoir wettability prediction method based on cross-scale data fusion according to the present invention.

[0054] Figure 4 shows a mineral surface model of the reservoir wettability prediction method based on cross-scale data fusion according to the present invention, wherein (a) is a calcium calcite surface model, and (b) is a 100% Fe 2+ Replace the calcite surface model diagram;

[0055] Figure 5 is a sodium chloride solution model diagram of a reservoir wettability prediction method based on cross-scale data fusion according to the present invention.

[0056] Figure 6 shows a calcite-sodium chloride solution model for a reservoir wettability prediction method based on cross-scale data fusion according to the present invention.

[0057] Figure 7 shows the final simulation results of the reservoir wettability prediction method based on cross-scale data fusion according to the present invention, wherein (a) is the simulation result of calcium calcite, and (b) is the simulation result of 100% Fe 2+ Simulation results of calcite replacement;

[0058] Figure 8 shows the relative concentration distribution curves (Z-direction) of solution molecules in the reservoir wettability prediction method based on cross-scale data fusion of the present invention. (a) is the relative concentration distribution curve of solution molecules in the calcium calcite system, and (b) is the relative concentration distribution curve of 100% Fe... 2+ Relative concentration distribution curves of molecules in the calcite-substituted system solution;

[0059] Figure 9 shows the mean square displacement curves and diffusion coefficients of solution molecules in the reservoir wettability prediction method based on cross-scale data fusion of the present invention. (a) shows the mean square displacement curves and diffusion coefficients of the calcium calcite system solution, and (b) shows the mean square displacement curves and diffusion coefficients of 100% Fe... 2+ Mean square displacement curves and diffusion coefficients of molecules in a solution with calcite substitution;

[0060] Figure 10 is a flowchart of molecular dynamics simulation in an embodiment of a reservoir wettability prediction method based on cross-scale data fusion according to the present invention.

[0061] Figure 11 shows a case study of the actual application of a reservoir wettability prediction method based on cross-scale data fusion in a well according to an embodiment of the present invention. Detailed Implementation

[0062] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0063] Secondly, the present invention is described in detail with reference to the schematic diagrams. When detailing the embodiments of the present invention, for ease of explanation, the cross-sectional views illustrating the device structure may be partially enlarged, not according to the usual scale. Furthermore, the schematic diagrams are merely examples and should not limit the scope of protection of the present invention. In addition, actual fabrication should include three-dimensional spatial dimensions of length, width, and depth.

[0064] To make the objectives, technical solutions, and advantages of the present invention clearer, the embodiments of the present invention will be described in further detail below with reference to the accompanying drawings.

[0065] This invention establishes an interaction model between mineral surfaces and fluids under different elemental substitution ratios at the molecular scale, obtaining a quantitative relationship between changes in mineral elemental composition and wettability. Furthermore, by combining this with in-well elemental logging curves, the degree of mineral ion substitution at different depths in the reservoir is calculated, thereby achieving continuous evaluation of wettability. This method combines microscopic simulation results with macroscopic logging information, establishing a unified evaluation method from microscopic analysis to macroscopic surfaces, solving the problem that existing methods cannot directly quantitatively calculate wettability from in-well elemental curves. This method is applicable not only to Ca in calcite provided in the case study but also... 2+ Fe 2+ The substitution method can also be extended to other mineral systems with isomorphous substitution or elemental doping, providing a basis for wettability studies of complex reservoirs and oil and gas development decisions, and has strong theoretical significance and engineering application value.

[0066] The technical terms used in this invention are explained as follows:

[0067] Wetness: refers to the affinity of a rock surface for different fluids, which can usually be characterized by parameters such as contact angle, adsorption energy, and water distribution characteristics.

[0068] Calcite: a common carbonate mineral whose main component is calcium carbonate (CaCO3), and is one of the common framework minerals in reservoirs.

[0069] Element substitution: refers to the process in which one ion or element in a crystal structure is partially or completely replaced by another ion or element. For example, Fe. 2+ Alternative Ca 2+ That is, calcium ions in the crystal lattice are replaced by ferrous ions.

[0070] Elemental logging: A logging method that obtains the elemental content or relative elemental content of a formation through well logging measurements.

[0071] XRD, or X-ray diffraction, is a non-destructive testing method that uses the coherent diffraction effect of X-rays with a crystal lattice to analyze the phase composition and crystal structure of a material.

[0072] Mineral inversion: Mineral inversion is a technical method that uses the analysis and processing of geophysical, geochemical and other data to infer information such as the types, contents and distribution of minerals in the ground or other research areas.

[0073] Molar mass: Molar mass is a physical unit, which is the mass of one unit amount of substance.

[0074] Molecular dynamics (MD) simulations are computational simulation methods based on the laws governing atomic and molecular motion, used to analyze the interactions between mineral surfaces and fluids. MD is an abbreviation for "Molecular Dynamics".

[0075] Reservoir wettability evaluation: A systematic analysis of the affinity relationship between reservoir rock surfaces and fluids such as oil and water is an important parameter for oil and gas development.

[0076] Element curves: These are curves showing the changes in the content of different elements with depth recorded in well logging, such as element curves for Ca, Fe, Mg, and Si.

[0077] NVT: An ensemble for molecular dynamics simulations, representing a constant number of particles (N), volume (V), and temperature (T). This ensemble is often used to study the thermal equilibrium state and structural evolution of systems under fixed volume conditions.

[0078] COMPASS II: A general set of empirical force field parameters applicable to molecular simulation calculations of organic, inorganic, and polymer systems, which can accurately describe intermolecular interactions and system energy changes.

[0079] Specifically, a reservoir wettability prediction method based on cross-scale data fusion is proposed. This method takes the main reservoir minerals as the research object, constructs mineral-fluid interface models under different element substitution ratios, uses molecular dynamics simulations to obtain the wettability variation law of mineral surfaces under different element contents, and then combines this law with well logging curves to achieve continuous calculation and quantitative evaluation of reservoir wettability. The method includes the following steps:

[0080] S1: Acquire and preprocess various logging data: First, acquire elemental logging data for the target reservoir interval. Elemental logging data should include at least Ca and Fe element curves; depending on the specific reservoir conditions, it may also include curves for Mg, Si, Al, K, Na, P, Ti, Mn, etc. Ca is mainly used to characterize the calcium component in carbonate minerals such as calcite and dolomite; Fe is mainly used to characterize iron components, iron ion substitution components, or iron cements; Mg can also be added later to distinguish between dolomite and magnesian calcite; Si, Al, K, etc., can be used to distinguish clay minerals. In addition to elemental logging data, the following data can be acquired simultaneously as auxiliary constraints: conventional logging data, including natural gamma, sonic transit time, density, neutron porosity, resistivity, etc.; core observation data, including lithology, color, fractures, pores and infill development; thin section identification data, including mineral composition, grain structure, cementation type and pore type; X-ray diffraction analysis data, i.e. XRD mineral composition analysis results; formation water salinity, ionic composition, temperature, pressure and other fluid and reservoir conditions.

[0081] Next, the logging data are preprocessed, including data screening, depth correction, outlier removal, and standardization of curve units. The preprocessing operation highlights the target layer data and makes different curves have a unified depth benchmark and comparability.

[0082] Based on the above data, the main reservoir mineral types in the target well section were determined, and it was determined whether the changes in the element content studied were mainly due to ion substitution within the target minerals.

[0083] S2: Identify target mineral types and determine elemental substitution relationships: Based on core, thin section, XRD, and well logging interpretation results, determine the main mineral types in the target reservoir and perform mineral inversion to obtain a continuous mineral content profile. Referring to this case, if calcite is the main mineral in the target section, then calcite will be the primary object for wettability evaluation. The chemical formula of calcite is CaCO3, and its crystal lattice contains Ca... 2+ The site can be replaced by a divalent metal ion with a similar radius or similar geochemical properties.

[0084] For example, Fe 2+ Mg 2+ All of these can enter the carbonate mineral lattice and affect the mineral surface electrical properties, hydration capacity, and oil-water adsorption state. Therefore, this study focuses on Fe. 2+ Alternatives to Ca in calcite 2+ For example, using Fe 2+ Alternative Ca 2+Subsequently, the changes in local charge distribution, surface hydroxylation state, water molecule orientation, and ion adsorption behavior on the calcite surface were investigated, and the influence of elemental alterations on the affinity of the calcite surface for the aqueous or oil phase was studied. For the target depth point Z, the Fe element in the target layer first needed to be corrected. Using XRD analysis and mineral inversion results, the Fe element corresponding to other iron-bearing minerals was proportionally subtracted, and the same applied to Ca. Then, for the target mineral calcite, the Fe content was calculated based on the Ca and Fe elemental contents. 2+ Relative to Ca 2+ The substitution ratio of a site can be expressed in the following form:

[0085] (2-1)

[0086] in, Indicates depth Fe 2+ For Ca 2+ The relative substitution ratio of sites, This indicates the molar content of Fe at that depth. This indicates the molar content of Ca at that depth.

[0087] S3: Well Mineral Sample Wettability Calibration: After determining the target mineral type and elemental substitution relationship, select depths in the target well section that have obvious elemental logging curve characteristics, relatively stable mineral composition, and can represent the target reservoir section. Obtain core samples corresponding to these depths and perform wettability tests on the samples. The specific calibration method is not limited; in this study, the contact angle method was selected for calibration.

[0088] First, based on elemental logging data, XRD mineral composition analysis results, and core observation results, the target depth point Z was selected. Core samples were obtained at this depth, and the sample surfaces were cut, polished, and cleaned to reduce the impact of mud contamination, oil residue, and surface roughness differences on the contact angle test results. After sample processing, contact angle experiments were conducted on the sample surface under set temperature and pressure conditions, as shown in Figure 1, to determine the contact angle of the aqueous phase on the sample surface. The specific calibration process requires multiple tests, each time selecting different surfaces of the sample to measure the wetting angle, and taking the average value as the final wetting angle result. Among these, the contact angle... It can be used to characterize the actual wettability of mineral samples at this depth. When the contact angle is small, it indicates that the sample surface has a strong affinity for the water phase, exhibiting strong hydrophilicity. When the contact angle is large, it indicates that the sample surface has a weak affinity for the water phase, exhibiting weak hydrophilicity, neutral wetting, or oily wetting characteristics.

[0089] Simultaneously, using the elemental logging results corresponding to depth point Z, the elemental substitution ratio in the target mineral at that depth is calculated using Equation 2-1. Therefore, the elemental substitution ratio at a certain depth in the well can be determined. Compared with the measured contact angle Establish a correspondence. This calibration step allows for the correlation between the elemental proportions in the well, molecular dynamics simulation parameters, and actual wettability test results, providing experimental constraints for the subsequent establishment of a continuous reservoir wettability evaluation model.

[0090] The calcite sample used in this calibration was not subjected to elemental substitution. The results of multiple tests are shown in Figure 2. The final wetting angle was 80.58°. According to SY / T5153-2007 "Method for Determination of Wettability of Reservoir Rocks", a water phase contact angle between 75° and 105° indicates neutral wetting and a certain degree of hydrophilicity.

[0091] S4: Establishing a Molecular Dynamics Simulation System for Mineral Research: After completing the above calibration, the next step is to conduct molecular-level simulations. First, a mineral model is established, specifically a calcite unit cell model based on the calcite crystal structure parameters. Calcite belongs to the trigonal crystal system and is mainly composed of Ca. 2+ and CO3 2- Group composition. During modeling, the calcite cell shown in Figure 3 can be imported from the crystal database and experimental cell parameters. After importing the cell, the original calcite cell needs to be geometrically optimized to achieve an energy-stable state. Then, the calcite surface model is formed by cutting along a specific crystal plane. In this study, the common cleavage plane (104) of calcite is selected for cutting. If needed, (001), (110) or other crystal planes can also be selected. After cutting the crystal plane, the surface model is expanded to obtain a sufficiently large surface size to avoid non-realistic interactions of droplets or fluid structures caused by periodic boundary conditions. The expansion factor can be determined according to the computational resources and simulation objectives. For example, a 5×5, 6×6 or larger surface supercell can be used.

[0092] Next, a vacuum layer is added to the established mineral surface. The specific thickness needs to be selected based on the thickness of the water layer in the subsequent simulation to ensure that the liquid can diffuse freely within it and reduce periodic effects. Then, Ca is added to the calcite model according to the set proportions. 2+ Replace with Fe 2+ The specific substitution ratio can be set to multiple discrete points, for example: the original calcite model, Fe 2+ The substitution ratio is 0%; low substitution model, Fe 2+ The substitution ratio is 30%; in the medium substitution model, Fe 2+ The substitution ratio is 50%; high substitution model, Fe 2 + The substitution ratio is 70%; in the complete substitution model, Fe 2+ The substitution ratio is 100%. For each substitution ratio, efforts should be made to ensure that Fe... 2+ Ca on the surface and near the surface 2+ The spatial distribution of the sites is representative, Fe2+ The replacement sites can be randomly replaced, and the final effect is shown in Figure 4. For the bottom layer atoms of the solid, they can be fixed or weakly constrained as needed to simulate the stability of the mineral substrate; the surface atoms can be allowed to move freely or be subject to less constraint to reflect the interface relaxation behavior.

[0093] After completion, a liquid model is constructed. The liquid model used in this simulation is a common underground sodium chloride solution. The concentration can be set according to the formation water salinity. An oil phase solution model can also be constructed later to further explore the mineral wetting characteristics. First, the sodium chloride unit cell and water molecule models are drawn, and then the sodium chloride solution is constructed. The final solution model is shown in Figure 5. It should be noted that the length and width of the solution model need to be consistent with the mineral model.

[0094] After both models are constructed, mineral models with different degrees of element substitution can be combined with the same solution model to ensure consistency of other variables within the system, ultimately resulting in the "solid-liquid-solid" model shown in Figure 6, with the calcite surface normal direction set as the Z-axis. After all construction work is completed, molecular geometry optimization should be performed on different model systems to release redundant intermolecular configurational stresses and obtain the lowest-energy stable structure, preparing for subsequent formal molecular dynamics simulations.

[0095] S5: Setting Molecular Dynamics Simulation Parameters and Performing Calculations: During the simulation, the interaction between the mineral and the fluid is described by a force field. Multiple force fields are available; COMPASS II is used for this simulation. Each atom in the system is assigned a corresponding charge. Before the molecular dynamics simulation, the system parameters need to be determined. The system type used in this simulation is NVT, the temperature is set to 298K, the pressure is set to default, the simulation step size is set to 1 fs, and the total simulation time is 100 ps. The simulation uses pristine calcium calcite and 100% Fe... 2+ Taking the replaced calcite as an example, the final simulation results are shown in Figure 7. In the future, parameters can be set according to the actual situation of the research target layer, such as increasing the system temperature and pressure with depth, and changing the simulation step size and simulation time according to the final purpose, so that the whole simulation gives a more realistic result.

[0096] S6: Analysis of wettability parameters under different substitution ratios: After completing the molecular dynamics equilibrium simulation, the water film method was used to analyze different Fe... 2+ The changes in wettability of calcite surface under different substitution ratios. The basic idea of ​​the water film method is that when a mineral surface has a strong affinity for water, water molecules will preferentially form a continuous and stable adsorbed water film on the mineral surface; when the hydrophilicity of the mineral surface weakens, the water film will become thinner, break, locally desorb, or even exhibit an island-like or discontinuous distribution. Therefore, the wettability of the mineral surface can be quantitatively evaluated by analyzing the coverage, enrichment, and stability of the water film on the mineral surface.

[0097] With raw calcium calcite and 100% Fe 2+ Taking the replaced calcite as an example, the relative concentration distribution of solution molecules in the vertical (Z-axis) direction after the system stabilizes is first statistically analyzed. Using the calcite surface as a reference zero point, the number distribution of solution molecules within different distance intervals is obtained. Then, the number of solution molecules in each distance interval is converted into relative concentration or number density, forming the relative concentration distribution curve of solution molecules as shown in Figure 8. In this curve, a significant water molecule enrichment peak is usually present near the calcite surface. The maximum value of this enrichment peak reflects the adsorption strength of solution molecules on the mineral surface. As the distance increases, the water molecule concentration gradually decreases and approaches the background concentration of the bulk solution. Based on this decrease process, the adsorption area and its boundary position on the calcite surface can be determined. This analysis result directly reflects the wettability of the mineral to the solution; a higher adsorption peak indicates stronger wettability, which can be used to preliminarily determine the wettability of the mineral. As shown in the figure, compared to the relative concentration distribution curve of water molecules in the original calcium calcite, the 100% Fe... 2+ The higher enrichment peak after replacement initially indicates that Fe 2+ Replace Ca 2+ The hydrophilicity of calcite becomes stronger in the rear.

[0098] After obtaining the spatial distribution characteristics of water molecules, mean square displacement analysis was further performed on the interfacial water molecules to calculate the different Fe... 2+ The diffusion coefficient of water molecules under the substitution ratio condition is shown in Figure 9. It is used to characterize the stability of the water film on the calcite surface and the degree of restriction on water molecule migration. Mean square displacement (MSD) represents the average of the squares of the particle displacement over a certain time interval. For interfacial water molecules, their MSD curve over the simulation time can be calculated based on molecular dynamics trajectories, and its expression is:

[0099] (6-1)

[0100] in for The displacement vector of water molecules at time . The position vector at the initial moment. This indicates that the average value is taken for multiple molecules and multiple time points.

[0101] Calculate the corresponding diffusion coefficient based on the slope of the MSD curve. Its expression is:

[0102] (6-2)

[0103] in For diffusion dimension, in a two-dimensional surface diffusion process, we can take... For diffusion processes in three-dimensional systems, one can take... In this calculation, we take .

[0104] The diffusion coefficient can determine the degree of restriction on the migration of water molecules at the interface: when the slope of the MSD curve is small and the diffusion coefficient is low, it indicates that water molecules are strongly bound on the calcite surface, and the interfacial water film structure is relatively stable; when the slope of the MSD curve is large and the diffusion coefficient is high, it indicates that water molecules migrate more freely on the surface, and the interfacial water film stability is weak. Therefore, the MSD curve and diffusion coefficient can serve as important evaluation criteria for the stability of the interfacial water film. With the development of Fe... 2+ If the diffusion coefficient of interfacial water molecules changes systematically due to changes in the substitution ratio, it indicates that the substitution of mineral lattice has caused changes in surface hydration characteristics, thereby affecting reservoir wettability.

[0105] S7: Establish Fe 2+ Quantitative relationship between substitution ratio and wettability: based on different Fe 2+ A molecular dynamics model of the mineral-fluid interface was constructed under the substitution ratio. Mean square displacement curves of interfacial molecules were extracted and fitted to obtain the diffusion coefficient, characterizing the migration ability and confinement degree of interfacial molecules. Simultaneously, the peak values ​​of strong adsorption peaks in the relative concentration distribution of interfacial molecules were extracted to characterize the interfacial enrichment intensity and adsorption strength. Combined with the corresponding Fe... 2+ Simulation results under different substitution ratios were used to establish Fe 2+ A quantitative model of the relationship between substitution ratio, interfacial dynamic characteristic parameters, and reservoir wettability:

[0106] (7-1)

[0107] (7-2)

[0108] in, For Fe 2+ The substitution ratio of the target cation in the mineral lattice, The diffusion coefficient of water molecules at the interface. The value represents the peak value of the strong adsorption peak in the relative concentration distribution curve of water molecules at the interface.

[0109] A total of five different substitution ratios of calcite were used to simulate its wettability. The specific results are shown in Table 1:

[0110] Table 1: Comparison of wettability test results

[0111]

[0112] The specific fitting calculation formula is as follows:

[0113] (7-3)

[0114] (7-4)

[0115] To further clarify the relationship between wettability and elemental composition, a comprehensive wettability evaluation index can be established, combining the aforementioned diffusion coefficient with the peak value of strong adsorption peaks, for quantitative characterization of different Fe elements. 2+ The change in wettability of reservoir mineral surfaces under different substitution ratios, wherein the comprehensive wettability evaluation index can be determined by the diffusion coefficient and the peak value of the strong adsorption peak:

[0116] (7-5)

[0117] in As a comprehensive wettability evaluation index, and These are the peak value and diffusion coefficient of the benchmark strong adsorption peak of the calibration mineral, respectively. This is how the calibration mineral... and The weighting coefficients are used to characterize the contribution of the strong adsorption peak value and the interfacial water molecule diffusion coefficient to the comprehensive wettability evaluation index. Generally speaking, Values ​​can be assigned based on the actual level of contribution.

[0118] Based on the simulation results, the weight parameters were assigned equal weights, and then... Furthermore, the mineral used in this calibration was the original calcite sample, and the final results are shown in Table 2:

[0119] Table 2: Comparison of Comprehensive Wettability Evaluation Indicators

[0120]

[0121] Based on the wettability of the initial mineral, when the diffusion coefficient Smaller and stronger adsorption peak value Enlarge When the diffusion coefficient increases, it indicates that the migration ability of interfacial water molecules on the mineral surface is weaker and more restricted, while the interfacial enrichment effect is stronger, indicating that a stable water film is more easily formed on the mineral surface and the reservoir has stronger hydrophilicity; when the diffusion coefficient increases... Larger and stronger adsorption peak value To become smaller, that is The smaller the value, the stronger the interfacial water molecule migration ability and the weaker the adsorption stability, the lower the stability of the water film on the mineral surface, and the weaker the hydrophilicity of the reservoir or the more oily and wet characteristics it exhibits.

[0122] This evaluation index Adjustments can be made based on the studied minerals and substitution elements. Further adjustments can be made using contact angle tests, self-absorption experiments, nuclear magnetic resonance experiments, core displacement experiments, or existing reservoir wettability test results to refine the comprehensive wettability evaluation index. Calibration is performed to establish the correspondence between the elemental substitution ratio, diffusion coefficient, peak value of strong adsorption peak and actual reservoir wettability, thereby forming a quantitative evaluation model applicable to the target reservoir with wide applicability.

[0123] S8: Establish wettability grading standards and output evaluation results: In establishing Fe... 2+ After quantifying the relationship between substitution ratio and wettability, for the target well section at a depth of The reservoir's Fe content at that depth can be determined based on mineral composition analysis and elemental testing results. 2+ Substitution ratio Then, by substituting these values ​​into the quantitative relationship model established in S7, we obtain the corresponding interfacial water molecule diffusion coefficient, strong adsorption peak value, and comprehensive wettability evaluation index:

[0124] (8-1)

[0125] (8-2)

[0126] (8-3)

[0127] in, For the target well depth The corresponding interfacial water molecule diffusion coefficient, For the target well depth The corresponding strong adsorption peak value. For the target well depth The comprehensive wettability evaluation index at the location. This allows for the determination of Fe content varying with depth in the target well section. 2+ The substitution ratio curve, diffusion coefficient curve, strong adsorption peak value curve, and comprehensive wettability evaluation curve enable continuous evaluation of reservoir wettability.

[0128] Finally, a comprehensive wettability evaluation index can be established for S6 based on the measured wettability results of typical reservoir samples. The reservoir wettability classification standard is established based on the calibration, and the continuous wettability evaluation results and wettability level distribution of the target well section are output. For specific well case studies, please refer to the example subsection.

[0129] In summary, this invention uses calcite as an example to construct different Fe... 2+A calcite crystal model under different substitution ratios was developed, and molecular dynamics simulations were used to obtain the wettability response results corresponding to different substitution ratios. Furthermore, a quantitative relationship between the substitution ratio and wettability evaluation indicators was established through mathematical fitting, enabling continuous quantitative evaluation of reservoir wettability. This method is applicable not only to Fe in calcite... 2+ Alternative Ca 2+ This method can also be applied to wettability evaluation under other mineral types, other element substitution methods, different substitution ratios, and different fluid environments, demonstrating strong versatility and scalability. Through this method, reservoir wettability can be directly calculated from well elemental and mineral composition data, overcoming the shortcomings of traditional methods such as reliance on core experiments, discrete evaluation results, and difficulty in characterizing the influence of changes in mineral microstructure. This provides a technical basis for underground reservoir evaluation and development scheme optimization.

[0130] The complete implementation process of this patented method is as follows: First, obtain elemental logging, mineral composition, and core analysis data for the target well section to determine the main wettability-sensitive minerals in the reservoir and the types and proportions of elements that can undergo ion substitution. Mineral inversion is then performed to obtain a continuous mineral content profile. Second, based on different substitution ratios, construct typical "mineral-fluid-mineral" interface models and conduct molecular dynamics simulations to obtain the fluid distribution and interfacial interaction characteristics on the mineral surface. Subsequently, statistically analyze the relative concentration distribution of solution molecules in the normal direction on the mineral surface to determine the enrichment degree and coverage of the adsorption film. The interfacial molecular diffusion coefficient is calculated using MSD analysis to evaluate the adsorption of the studied minerals to the solution. Furthermore, establish a quantitative relationship between the element substitution ratio and wettability parameters. Finally, substitute the original logging results into the model to generate a continuous reservoir wettability evaluation curve and complete the classification.

[0131] The molecular dynamics simulation workflow comprises four stages: preprocessing, model processing, data acquisition and analysis, and result output. First, in the preprocessing stage, the solid surface, liquid type, and simulation method are selected to construct molecular models of the substance and liquid. Furthermore, material interface and fluid models are established, a vacuum layer is added, and the environmental force field is configured. Second, in the model processing stage, simulation parameters are set, including time step, spatial coordinates, temperature, and pressure. Then, dynamic simulations are performed, and the system energy is optimized and balanced to obtain a stable system model. Subsequently, in the data acquisition and analysis stage, data such as equilibrium system snapshots, relative molecular concentration distributions, radial distribution function plots, and mean square displacement plots are extracted. Finally, the obtained results are output and analyzed to evaluate interfacial interactions, molecular distribution, and diffusion characteristics.

[0132] The specific workflow of molecular dynamics simulation is shown in Figure 10.

[0133] Taking a certain well as an example, a specific implementation case of the method of the present invention is shown:

[0134] The well data is relatively comprehensive, with input curves including natural gamma ray logging, sonic transit time logging, compensated neutron logging, compensated density logging, and elemental logging. First, the target carbonate formation was selected based on the logging lithology profile. Then, mineral inversion was performed using core XRD data to obtain the formation's mineral composition and content.

[0135] Subsequently, for any depth point, the Fe element content at that depth can be obtained from the elemental logging curve and converted into Fe molar amounts. Then, combined with XRD mineral composition, thin section identification, or well logging mineral interpretation results, the Fe element contained in non-calcite minerals is subtracted to obtain the Fe molar amounts that may enter the calcite lattice. Similarly, the same processing is performed on Ca to obtain the Ca element content in the calcite lattice. Finally, the ratio of the Fe molar amounts entering the calcite lattice to the total number of calcite cation sites is calculated to obtain the Fe content in the calcite at that depth. 2+ Alternative Ca 2+ The proportion.

[0136] Next, the interfacial water molecule diffusion coefficient, strong adsorption peak value, and comprehensive wettability evaluation index for each point were calculated. The results are shown in Figure 11, where the seventh line represents the calculated wettability parameters, the eighth line represents the wettability grade classification results, and the ninth line indicates carbonate rocks. Specific classification thresholds are shown in Table 3. As shown in Table 3, rock wettability can be divided into 6 levels based on the comprehensive wettability index W. With increasing W value, the rock surface wettability gradually changes from hydrophobic to hydrophilic, indicating that the interfacial water molecule adsorption strength and overall wettability characteristics gradually increase. When W <= -0.5, the rock exhibits the weakest wettability and obvious hydrophobic characteristics; when W > 1.0, the rock exhibits the strongest wettability and significant hydrophilic characteristics. Subsequent wettability evaluation indices and classification thresholds can be adjusted based on experimental or regional data.

[0137] Table 3: Based on comprehensive wettability index Example of wettability grading threshold

[0138]

[0139] Although the present invention has been described above with reference to embodiments, various modifications can be made and components can be replaced with equivalents without departing from the scope of the invention. In particular, as long as there is no structural conflict, the features in the disclosed embodiments can be combined with each other in any manner. The lack of an exhaustive description of these combinations in this specification is merely for the sake of brevity and resource conservation. Therefore, the present invention is not limited to the specific embodiments disclosed herein, but includes all technical solutions falling within the scope of the claims.

Claims

1. A reservoir wettability prediction method based on cross-scale data fusion, characterized in that, Includes the following steps: S1: Collect and preprocess various logging data: determine the main reservoir mineral types and determine whether the changes in element content mainly come from ion substitution within the target mineral; S2: Identify target mineral types and determine elemental substitution relationships: perform mineral inversion to obtain a continuous mineral content profile; S3: Wetness calibration of mineral samples in wells: Screen the depth positions of elemental logging curves, obtain core samples, and perform wettability tests on the samples; S4: Establish a molecular dynamics simulation system for studying minerals: establish mineral models and liquid models, and combine mineral models with different degrees of element substitution with the same solution model respectively; S5: Set molecular dynamics simulation parameters and perform calculations; S6: Analysis of wettability parameters under different substitution ratios: The water film method was used to analyze different Fe... 2+ Changes in the wettability of calcite surface at different substitution ratios; S7: Establish Fe 2+ Quantitative relationship between substitution ratio and wettability: based on different Fe 2+ A molecular dynamics model of the mineral-fluid interface was constructed under the substitution ratio. The mean square displacement curves of the interface molecules were extracted and fitted to obtain the diffusion coefficient. The peak values ​​of strong adsorption peaks in the relative concentration distribution of interface molecules were extracted. Combined with the corresponding Fe... 2+ Based on the simulation results under the substitution ratio, a quantitative relationship model is established; S8: Establish wettability grading standards and output evaluation results: Obtain Fe based on mineral composition analysis results and elemental test results. 2+ Substitution ratio Substituting these values ​​into the quantitative relationship model yields a comprehensive wettability evaluation index.

2. The reservoir wettability prediction method based on cross-scale data fusion according to claim 1, characterized in that, In S1, the collected logging data are elemental logging data, including at least: Ca element curves and Fe element curves; depending on the specific reservoir conditions, they also include Mg, Si, Al, K, Na, P, Ti, and Mn element curves; conventional logging data: including natural gamma ray, sonic transit time, density, neutron porosity, and resistivity; core observation data: including lithology, color, fractures, pores, and infill development; thin section identification data: including mineral composition, grain structure, cementation type, and pore type; X-ray diffraction analysis data, i.e., XRD mineral composition analysis results; formation water salinity, ionic composition, temperature, pressure, fluid, and reservoir conditions; The preprocessing specifically includes data filtering, depth correction, outlier removal, and curve unit unification. Through preprocessing operations, the target layer data is highlighted, and different curves have a unified depth benchmark and comparability.

3. The reservoir wettability prediction method based on cross-scale data fusion according to claim 1, characterized in that, The specific method of S2 is as follows: For the target depth point Z, the Fe element of the target layer first needs to be corrected. Using XRD analysis and mineral inversion results, the Fe element corresponding to other iron-bearing minerals is proportionally subtracted, and the same applies to Ca. Subsequently, for the target mineral calcite, the Fe is calculated based on the Ca and Fe element contents. 2+ Relative to Ca 2+ The substitution ratio of the sites is expressed in the following form: (2-1) in, Indicates depth Fe 2+ For Ca 2+ The relative substitution ratio of sites, This indicates the molar content of Fe at that depth. This indicates the molar content of Ca at that depth.

4. The reservoir wettability prediction method based on cross-scale data fusion according to claim 1, characterized in that, The specific method of S3 is as follows: First, based on elemental logging data, XRD mineral composition analysis results, and core observation results, a target depth point Z is selected; a core sample is obtained at this depth, and the sample surface is cut, polished, and cleaned. After sample processing, a contact angle experiment is conducted on the sample surface under set temperature and pressure conditions to determine the contact angle of the aqueous phase on the sample surface. The specific calibration process requires multiple tests, each time selecting different surfaces of the sample to measure the wetting angle, and taking the average value as the final wetting angle result. Among these, the contact angle... This is used to characterize the actual wettability of mineral samples at this depth; simultaneously, using the elemental logging results corresponding to this depth point Z, the elemental substitution ratio in the target mineral at this depth is calculated using Equation 2-1; thus, the elemental substitution ratio at a certain depth in the well is determined. Compared with the measured contact angle Establish corresponding relationships.

5. The reservoir wettability prediction method based on cross-scale data fusion according to claim 1, characterized in that, The method for constructing the mineral model in S4 is as follows: a calcite cell model is established based on the calcite crystal structure parameters. The calcite cell is imported from the crystal database and experimental cell parameters. After importing the cell, the original calcite cell needs to be geometrically optimized to make the crystal structure reach an energy stable state. Then, the calcite surface model is formed by cutting along a specific crystal plane. Next, a vacuum layer is added to the established mineral surface.

6. The reservoir wettability prediction method based on cross-scale data fusion according to claim 1, characterized in that, The specific method of S6 is as follows: using raw calcium calcite and 100% Fe 2+ Taking the replaced calcite as an example, firstly, the relative concentration distribution of solution molecules in the vertical direction after the system stabilizes is statistically analyzed. Using the calcite surface as a reference zero point, the number distribution of solution molecules within different distance intervals is obtained. Then, the number of solution molecules within each distance interval is converted into relative concentration or number density, forming a relative concentration distribution curve of solution molecules, thus determining the adsorption region and its boundary position on the calcite surface. After obtaining the spatial distribution characteristics of water molecules, mean square displacement analysis is further performed on the interfacial water molecules to calculate the relative concentration distribution of different Fe atoms. 2+ The diffusion coefficient of water molecules under the substitution ratio condition is calculated based on the mean square displacement (MSD) curve over the simulation time using molecular dynamics trajectories. Its expression is: (6-1) in for The displacement vector of water molecules at time . The position vector at the initial moment. This indicates an overall average over multiple molecules and multiple time points; Calculate the corresponding diffusion coefficient based on the slope of the MSD curve. Its expression is: (6-2) in For the diffusion dimension.

7. The reservoir wettability prediction method based on cross-scale data fusion according to claim 1, characterized in that, The specific method of S7 is as follows: (7-1) (7-2) in, For Fe 2+ The substitution ratio of the target cation in the mineral lattice, The diffusion coefficient of water molecules at the interface. The peak value of the strong adsorption peak in the relative concentration distribution curve of water molecules at the interface; The specific formula for fitting calculation is as follows: (7-3) (7-4) A comprehensive wettability evaluation index is established, combining the above diffusion coefficient with the peak value of strong adsorption, for quantitative characterization of different Fe... 2+ The changes in wettability of reservoir mineral surfaces under different substitution ratios are evaluated by a comprehensive wettability assessment index determined jointly by the diffusion coefficient and the peak value of the strong adsorption peak. (7-5) in As a comprehensive wettability evaluation index, and These represent the peak value and diffusion coefficient of the benchmark strong adsorption peak of the calibration mineral, respectively. and The weighting coefficients are used to characterize the contribution of the strong adsorption peak value and the interfacial water molecule diffusion coefficient to the comprehensive wettability evaluation index.

8. The reservoir wettability prediction method based on cross-scale data fusion according to claim 1, characterized in that, The specific method of S8 is as follows: (8-1) (8-2) (8-3) in, For the target well depth The corresponding interfacial water molecule diffusion coefficient, For the target well depth The corresponding strong adsorption peak value. For the target well depth The comprehensive wettability evaluation index at the location; thus forming the Fe content of the target well section varying with depth. 2+ Substitution ratio curve, diffusion coefficient curve, strong adsorption peak value curve, and comprehensive wettability evaluation curve enable continuous evaluation of reservoir wettability. Based on the measured wettability results of typical reservoir samples, a comprehensive wettability evaluation index was established for S6. The reservoir wettability classification standard is established based on the calibration, and the continuous wettability evaluation results and wettability grade distribution of the target well section are output.

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