Gas reservoir residual gas distribution prediction method based on three-dimensional geological modeling and numerical simulation

Abstract

The invention discloses a gas reservoir residual gas distribution prediction method based on three-dimensional geological modeling and numerical simulation. The method comprises the following steps: S1, acquiring basic data of a gas well; s2, performing block geologic feature research, block development status analysis and production dynamic analysis by using the basic data of the gas well to obtain main control factors of gas well production; s3, establishing a gas well three-dimensional numerical model, and analyzing a relationship between gas well pressure and time according to gas well production main control factors; the natural decline rate and the comprehensive decline rate of the research area are calculated through an Arps decline method; s4, historical fitting verification is simulated according to the relation between gas well pressure and time, the natural declining rate and the comprehensive declining rate; and S5, through a verification result, carrying out gas reservoir residual gas distribution prediction. According to the gas reservoir residual gas distribution prediction method based on three-dimensional geological modeling and numerical simulation, the problem that residual gas of a tight sandstone gas reservoir cannot be predicted in the prior art is solved.

Description

Technical Field

[0001] This invention belongs to the field of low-permeability tight gas reservoir development technology, specifically involving a method for predicting the distribution of residual gas in gas reservoirs based on three-dimensional geological modeling and numerical simulation. Background Technology

[0002] Currently, the prediction of the remaining gas distribution in gas reservoirs mainly relies on geological research and geophysical data analysis. This involves in-depth analysis of the reservoir's heterogeneity, physical properties, and fluid distribution, and the application of gas reservoir engineering methods or numerical simulation methods, combined with parameters such as formation pressure and gas well production, to evaluate the utilization of natural gas and thus predict the distribution of remaining gas.

[0003] The Shenmu gas field is a tight sandstone gas reservoir with complex geological conditions, poor reservoir properties, and strong heterogeneity. This makes it difficult for traditional geological research methods to fully and accurately reflect the actual situation of the reservoir, and increases the uncertainty of numerical simulation in predicting fluid flow in reservoir pores. As a result, well location deployment and tracking adjustments are difficult. It is urgent to strengthen the study of regional geological characteristics, deepen the research and analysis of three-dimensional geological modeling and numerical simulation, improve the accuracy of remaining gas distribution prediction, implement production in favorable areas, and rationally deploy well networks to provide guidance for production capacity construction and development adjustments. Summary of the Invention

[0004] The purpose of this invention is to provide a method for predicting the distribution of residual gas in gas reservoirs based on three-dimensional geological modeling and numerical simulation, which solves the problem that existing technologies cannot predict the residual gas in tight sandstone gas reservoirs.

[0005] The technical solution adopted in this invention is a method for predicting the distribution of residual gas in gas reservoirs based on three-dimensional geological modeling and numerical simulation, comprising the following steps: S1. Obtain basic data on gas wells; S2. Utilize basic gas well data to study the geological characteristics of the block, analyze the current development status of the block, and analyze production dynamics to determine the main controlling factors of gas well production. S3. Establish a three-dimensional numerical model of the gas well, analyze the relationship between gas well pressure and time based on the main factors controlling gas well production, and calculate the natural decline rate and comprehensive decline rate of the study area using the Arps decline method. S4. Historical fitting verification based on the relationship between gas well pressure and time, natural decline rate and comprehensive decline rate; S5. Based on the verification results, predict the distribution of remaining gas in the gas reservoir.

[0006] The invention is further characterized by: The basic data in S1 includes core samples, outcrops, logging data, test data, and production data.

[0007] The specific process of S2 is as follows: using basic gas well data, the geological characteristics of the block's lithology, physical properties, gas-bearing properties, and the sedimentary microfacies and sand body distribution of the potential layer are studied; using basic gas well data, the current status of the block's development is analyzed, including development dynamics, production capacity, formation pressure, decline patterns, reserve recalculation, and utilization level; using basic gas well data, the overall production dynamics of the gas wells already in production are analyzed, including their overall location, layer position, and well type.

[0008] The specific process of production dynamic analysis is as follows: using basic gas well data, the single-production wells in the study area are classified according to the current daily gas production, pressure drop rate and historical gas production change trends of each well. The main controlling factors of gas well production are obtained by the relationship between the distribution of each type of well and the distribution of pressure coefficient, paleogeography, structure and gas reservoir.

[0009] The specific process of establishing a three-dimensional numerical model of a gas well in S3 is as follows: Step 1: Establish a three-dimensional structural model that includes a fault network model, a stratigraphic model, and a geological body model. The three-dimensional structural model should reflect the geometric shape of the geological structure and the macroscopic contact relationship between various structural geological elements. The three-dimensional structural model includes the relationship between faults, strata, and faults. Step 2: Establish a sedimentary microfacies model. The sedimentary microfacies model must conform to the actual situation of subsurface space, spatial distribution of sedimentary facies, and facies combination. The sedimentary microfacies model adopts two methods: deterministic modeling and stochastic modeling. Stochastic modeling uses well point data as control points, assuming that parameters outside the control points have random distribution characteristics, and selects appropriate stochastic functions to model the sedimentary facies. Step 3: Establish phase-controlled property model; The phase-controlled property model needs to consider the sedimentary microfacies to which the physical property parameter points belong. The phase-controlled property model is simulated in different categories to obtain the distribution of physical properties in three-dimensional space.

[0010] The specific process for calculating the natural decline rate and the overall decline rate of the study area using the Arps decline method in S3 is as follows: Calculate the natural decline rate and the comprehensive decline rate according to equations (1), (2) and (3); (1); (2); (3); in, Q i The initial production rate during the decline phase, in units of 10⁴ m³. 3 / mon or 108m 3 / year; Q The output at any time during the decline phase, in units of 10⁴ m³. 3 / mon or 108m 3 / year; D The instantaneous decline rate is expressed in units of 1 / month or 1 / year. D i The initial instantaneous decrease rate during the decrease, in units of 1 / mon or 1 / year; q i This represents the gas field's annual output. q ’ i This refers to the output of the measures taken that year; q" i This refers to the output of new wells that year; D n This is the natural decline rate; D R The overall decline rate; D This represents the total decrease rate.

[0011] The specific process of S4 is as follows: S4.1. Based on the geological model, and combined with the historical production dynamics of the gas reservoir and single wells, establish a numerical simulation model; S4.2 Utilize numerical simulation models for historical fitting and reserve verification, and fit the production history of the block; The specific process is as follows: correct the three-dimensional numerical model of the gas well and the core fluid experimental data to make the model calculation dynamics consistent with the actual production dynamics, and understand the current residual gas distribution status of the reservoir based on the calculation results of the corrected model after historical fitting. The specific process of history fitting is as follows: The first step is to determine the objective of the history fitting process; The second step is to select a historical fitting method based on the historical fitting target, company resources, fitting period, and data reliability. The third step is to determine the historical production data to be fitted and the criteria for successful fitting. Step 4: Determine the adjustable reservoir data and reliable range during the historical fitting process; Step 5: Run the simulation model using the most reliable input data; Step 6: Compare the historical fitting results with the production data selected in Step 3; Step 7: Within a reliable range, vary the reservoir data selected in Step 4; Step 8: Repeat steps 5 through 7 until the fitting criteria in step 3 are met, and obtain the verification results.

[0012] The beneficial effects of this invention are: The present invention provides a method for predicting the distribution of residual gas in gas reservoirs based on three-dimensional geological modeling and numerical simulation. It utilizes high-resolution sequence stratigraphy theory to complete the sub-layer division and the identification and characterization of individual sand bodies within sub-layers; it utilizes sedimentology and reservoir configuration theory to complete the quantitative prediction of sand body configuration, superposition relationship, spatial distribution and high-quality reservoirs; based on three-dimensional numerical simulation research, it quantitatively predicts the spatial distribution law of formation pressure and residual gas saturation, providing geological guidance for new well deployment and development plan adjustment. Detailed Implementation

[0013] The present invention will now be described in detail with reference to specific embodiments.

[0014] Example 1 The gas reservoir residual gas distribution prediction method based on three-dimensional geological modeling and numerical simulation proposed in this embodiment includes the following steps: S1. Obtain basic data on gas wells; S2. Utilize basic gas well data to study the geological characteristics of the block, analyze the current development status of the block, and analyze production dynamics to determine the main controlling factors of gas well production. S3. Establish a three-dimensional numerical model of the gas well, analyze the relationship between gas well pressure and time based on the main factors controlling gas well production, and calculate the natural decline rate and comprehensive decline rate of the study area using the Arps decline method. S4. Historical fitting verification based on the relationship between gas well pressure and time, natural decline rate and comprehensive decline rate; S5. Based on the verification results, predict the distribution of remaining gas in the gas reservoir.

[0015] Example 2 The gas reservoir residual gas distribution prediction method based on three-dimensional geological modeling and numerical simulation proposed in this embodiment includes the following steps: S1. Obtain basic data on gas wells; Basic data includes core samples, outcrops, logging data, test data, and production data; S2. Utilize basic gas well data to study the geological characteristics of the block, analyze the current development status of the block, and analyze production dynamics to determine the main controlling factors of gas well production. The specific process is as follows: using basic gas well data, the geological characteristics of the block's lithology, physical properties, gas-bearing properties, and the sedimentary microfacies and sand body distribution of the potential layer are studied; using basic gas well data, the current development status of the block, including development dynamics, production capacity, formation pressure, decline patterns, reserve recalculation, and utilization level, are analyzed; using basic gas well data, the overall production dynamics of the gas wells in production, as well as their layer locations and well types, are analyzed. The specific process of production dynamic analysis is as follows: using basic gas well data, the single production wells in the study area are classified according to the current daily gas production, pressure drop rate and historical gas production change trend of single wells. The main control factors of gas well production are obtained by the relationship between the distribution of various types of wells and the distribution of pressure coefficients, paleogeography, structural distribution and gas reservoir distribution. S3. Establish a three-dimensional numerical model of the gas well, analyze the relationship between gas well pressure and time based on the main factors controlling gas well production, and calculate the natural decline rate and comprehensive decline rate of the study area using the Arps decline method. S4. Historical fitting verification based on the relationship between gas well pressure and time, natural decline rate and comprehensive decline rate; S5. Based on the verification results, predict the distribution of remaining gas in the gas reservoir.

[0016] Example 3 The gas reservoir residual gas distribution prediction method based on three-dimensional geological modeling and numerical simulation proposed in this embodiment includes the following steps: S1. Obtain basic data on gas wells; Basic data includes core samples, outcrops, logging data, test data, and production data; S2. Utilize basic gas well data to study the geological characteristics of the block, analyze the current development status of the block, and analyze production dynamics to determine the main controlling factors of gas well production. The specific process is as follows: using basic gas well data, the geological characteristics of the block's lithology, physical properties, gas-bearing properties, and the sedimentary microfacies and sand body distribution of the potential layer are studied; using basic gas well data, the current development status of the block, including development dynamics, production capacity, formation pressure, decline patterns, reserve recalculation, and utilization level, are analyzed; using basic gas well data, the overall production dynamics of the gas wells in production, as well as their layer locations and well types, are analyzed. The specific process of production dynamic analysis is as follows: using basic gas well data, the single production wells in the study area are classified according to the current daily gas production, pressure drop rate and historical gas production change trend of single wells. The main control factors of gas well production are obtained by the relationship between the distribution of various types of wells and the distribution of pressure coefficients, paleogeography, structural distribution and gas reservoir distribution. S3. Establish a three-dimensional numerical model of the gas well, analyze the relationship between gas well pressure and time based on the main factors controlling gas well production, and calculate the natural decline rate and comprehensive decline rate of the study area using the Arps decline method. The specific process of establishing a three-dimensional numerical model of a gas well is as follows: Step 1: Establish a three-dimensional structural model that includes a fault network model, a stratigraphic model, and a geological body model. The three-dimensional structural model should reflect the geometric shape of the geological structure and the macroscopic contact relationship between various structural geological elements. The three-dimensional structural model includes the relationship between faults, strata, and faults. Step 2: Establish a sedimentary microfacies model. The sedimentary microfacies model must conform to the actual situation of subsurface space, spatial distribution of sedimentary facies, and facies combination. The sedimentary microfacies model adopts two methods: deterministic modeling and stochastic modeling. Stochastic modeling uses well point data as control points, assuming that parameters outside the control points have random distribution characteristics, and selects appropriate stochastic functions to model the sedimentary facies. Step 3: Establish phase-controlled property model; The phase-controlled property model needs to consider the sedimentary microfacies to which the physical property parameter points belong. The phase-controlled property model is simulated in different categories to obtain the distribution of physical properties in three-dimensional space. The specific process of calculating the natural decline rate and the combined decline rate of the study area using the Arps decline method is as follows: Calculate the natural decline rate and the comprehensive decline rate according to equations (1), (2) and (3); (1); (2); (3); in, Q i The initial production rate during the decline phase, in units of 10⁴ m³. 3 / mon or 108m 3 / year; Q The output at any time during the decline phase, in units of 10⁴ m³. 3 / mon or 108m 3 / year; D The instantaneous decline rate is expressed in units of 1 / month or 1 / year. D i The initial instantaneous decrease rate during the decrease, in units of 1 / mon or 1 / year; q i This represents the gas field's annual output. q ’ i This refers to the output of the measures taken that year; q" i This refers to the output of new wells that year; D n This is the natural decline rate; D R The overall decline rate; D The total decline rate; S4. Historical fitting verification based on the relationship between gas well pressure and time, natural decline rate and comprehensive decline rate; S5. Based on the verification results, predict the distribution of remaining gas in the gas reservoir.

[0017] Example 4 The gas reservoir residual gas distribution prediction method based on three-dimensional geological modeling and numerical simulation proposed in this embodiment includes the following steps: S1. Obtain basic data on gas wells; Basic data includes core samples, outcrops, logging data, test data, and production data; S2. Utilize basic gas well data to study the geological characteristics of the block, analyze the current development status of the block, and analyze production dynamics to determine the main controlling factors of gas well production. The specific process is as follows: using basic gas well data, the geological characteristics of the block's lithology, physical properties, gas-bearing properties, and the sedimentary microfacies and sand body distribution of the potential layer are studied; using basic gas well data, the current development status of the block, including development dynamics, production capacity, formation pressure, decline patterns, reserve recalculation, and utilization level, are analyzed; using basic gas well data, the overall production dynamics of the gas wells in production, as well as their layer locations and well types, are analyzed. The specific process of production dynamic analysis is as follows: using basic gas well data, the single production wells in the study area are classified according to the current daily gas production, pressure drop rate and historical gas production change trend of single wells. The main control factors of gas well production are obtained by the relationship between the distribution of various types of wells and the distribution of pressure coefficients, paleogeography, structural distribution and gas reservoir distribution. S3. Establish a three-dimensional numerical model of the gas well, analyze the relationship between gas well pressure and time based on the main factors controlling gas well production, and calculate the natural decline rate and comprehensive decline rate of the study area using the Arps decline method. The specific process of establishing a three-dimensional numerical model of a gas well is as follows: Step 1: Establish a three-dimensional structural model that includes a fault network model, a stratigraphic model, and a geological body model. The three-dimensional structural model should reflect the geometric shape of the geological structure and the macroscopic contact relationship between various structural geological elements. The three-dimensional structural model includes the relationship between faults, strata, and faults. Step 2: Establish a sedimentary microfacies model. The sedimentary microfacies model must conform to the actual situation of subsurface space, spatial distribution of sedimentary facies, and facies combination. The sedimentary microfacies model adopts two methods: deterministic modeling and stochastic modeling. Stochastic modeling uses well point data as control points, assuming that parameters outside the control points have random distribution characteristics, and selects appropriate stochastic functions to model the sedimentary facies. Step 3: Establish phase-controlled property model; The phase-controlled property model needs to consider the sedimentary microfacies to which the physical property parameter points belong. The phase-controlled property model is simulated in different categories to obtain the distribution of physical properties in three-dimensional space. The specific process of calculating the natural decline rate and the combined decline rate of the study area using the Arps decline method is as follows: Calculate the natural decline rate and the comprehensive decline rate according to equations (1), (2) and (3); (1); (2); (3); in, Q i The initial production rate during the decline phase, in units of 10⁴ m³. 3 / mon or 108m 3 / year; Q The output at any time during the decline phase, in units of 10⁴ m³. 3 / mon or 108m 3 / year; D The instantaneous decline rate is expressed in units of 1 / month or 1 / year. D i The initial instantaneous decrease rate during the decrease, in units of 1 / mon or 1 / year; q i This represents the gas field's annual output. q ’ i This refers to the output of the measures taken that year; q" i This refers to the output of new wells that year; D n This is the natural decline rate; D R The overall decline rate; D The total decline rate; S4. Historical fitting verification based on the relationship between gas well pressure and time, natural decline rate and comprehensive decline rate; The specific process is as follows: S4.1. Based on the geological model, and combined with the historical production dynamics of the gas reservoir and single wells, establish a numerical simulation model; S4.2 Utilize numerical simulation models for historical fitting and reserve verification, and fit the production history of the block; The specific process is as follows: correct the three-dimensional numerical model of the gas well and the core fluid experimental data to make the model calculation dynamics consistent with the actual production dynamics, and understand the current residual gas distribution status of the reservoir based on the calculation results of the corrected model after historical fitting. The specific process of history fitting is as follows: The first step is to determine the objective of the history fitting process; The second step is to select a historical fitting method based on the historical fitting target, company resources, fitting period, and data reliability. The third step is to determine the historical production data to be fitted and the criteria for successful fitting. Step 4: Determine the adjustable reservoir data and reliable range during the historical fitting process; Step 5: Run the simulation model using the most reliable input data; Step 6: Compare the historical fitting results with the production data selected in Step 3; Step 7: Within a reliable range, vary the reservoir data selected in Step 4; Step 8: Repeat steps 5 through 7 until the fitting criteria in step 3 are met, and obtain the verification results; S5. Based on the verification results, predict the distribution of remaining gas in the gas reservoir.

Claims

1. A method for predicting the distribution of residual gas in gas reservoirs based on three-dimensional geological modeling and numerical simulation, characterized in that, Includes the following steps: S1. Obtain basic data on gas wells; S2. Utilize basic gas well data to study the geological characteristics of the block, analyze the current development status of the block, and analyze production dynamics to determine the main controlling factors of gas well production. S3. Establish a three-dimensional numerical model of the gas well, analyze the relationship between gas well pressure and time based on the main factors controlling gas well production, and calculate the natural decline rate and comprehensive decline rate of the study area using the Arps decline method. S4. Historical fitting verification based on the relationship between gas well pressure and time, natural decline rate and comprehensive decline rate; S5. Based on the verification results, predict the distribution of remaining gas in the gas reservoir.

2. The method for predicting the distribution of residual gas in a gas reservoir based on three-dimensional geological modeling and numerical simulation according to claim 1, characterized in that, The basic data mentioned in S1 includes core samples, outcrops, logging data, test data, and production data.

3. The method for predicting the distribution of residual gas in a gas reservoir based on three-dimensional geological modeling and numerical simulation according to claim 1, characterized in that, The specific process of S2 is as follows: using basic gas well data, the geological characteristics of the block's lithology, physical properties, gas-bearing properties, and the sedimentary microfacies and sand body distribution of the potential layer are studied; using basic gas well data, the current status of the block's development is analyzed, including development dynamics, production capacity, formation pressure, decline patterns, reserve recalculation, and utilization level; using basic gas well data, the overall production dynamics of the gas wells already in production are analyzed, including their overall location, layer position, and well type.

4. The method for predicting the distribution of residual gas in a gas reservoir based on three-dimensional geological modeling and numerical simulation according to claim 3, characterized in that, The specific process of the production dynamic analysis is as follows: using basic gas well data, the single-production wells in the study area are classified according to the current daily gas production, pressure drop rate and historical gas production change trends of each well. The main controlling factors of gas well production are obtained by the relationship between the distribution of each type of well and the distribution of pressure coefficient, paleogeography, structure and gas reservoir.

5. The method for predicting the distribution of residual gas in a gas reservoir based on three-dimensional geological modeling and numerical simulation according to claim 1, characterized in that, The specific process for establishing a three-dimensional numerical model of a gas well, as described in S3, is as follows: Step 1: Establish a three-dimensional structural model that includes a fault network model, a stratigraphic model, and a geological body model. The three-dimensional structural model should reflect the geometric shape of the geological structure and the macroscopic contact relationship between various structural geological elements. The three-dimensional structural model includes the relationship between faults, between strata, and between faults and strata. Step 2: Establish a sedimentary microfacies model. The sedimentary microfacies model must conform to the actual situation of subsurface space, spatial distribution of sedimentary facies, and facies combination. The sedimentary microfacies model adopts both deterministic and stochastic modeling methods. The stochastic modeling uses well point data as control points, assuming that parameters outside the control points have random distribution characteristics, and selects an appropriate stochastic function to model the sedimentary facies. Step 3: Establish a phase-controlled property model; the phase-controlled property model needs to consider the sedimentary microfacies to which the physical property parameter points belong. The phase-controlled property model is simulated in different categories to obtain the distribution of physical properties in three-dimensional space.

6. The method for predicting the distribution of residual gas in a gas reservoir based on three-dimensional geological modeling and numerical simulation according to claim 1, characterized in that, The specific process described in S3 for calculating the natural decline rate and the overall decline rate of the study area using the Arps decline method is as follows: Calculate the natural decline rate and the comprehensive decline rate according to equations (1), (2) and (3); （1）； （2）； （3）； in, Q i The initial production rate during the decline phase, in units of 10⁴ m³. 3 / mon or 108m 3 / year; Q The output at any time during the decline phase, in units of 10⁴ m³. 3 / mon or 108m 3 / year; D The instantaneous decline rate is expressed in units of 1 / month or 1 / year. D i The initial instantaneous decrease rate during the decrease, in units of 1 / mon or 1 / year; q i This represents the gas field's annual output. q ’ i This refers to the output of the measures taken that year; q" i This refers to the output of new wells that year; D n This is the natural decline rate; D R The overall decline rate; D This represents the total decrease rate.

7. The method for predicting the distribution of residual gas in a gas reservoir based on three-dimensional geological modeling and numerical simulation according to claim 1, characterized in that, The specific process of S4 is as follows: S4.

1. Based on the geological model, and combined with the historical production dynamics of the gas reservoir and single wells, establish a numerical simulation model; S4.2 Utilize numerical simulation models for historical fitting and reserve verification, and fit the production history of the block; The specific process is as follows: correct the three-dimensional numerical model of the gas well and the core fluid experimental data to make the model calculation dynamics consistent with the actual production dynamics, and understand the current residual gas distribution status of the reservoir based on the calculation results of the corrected model after historical fitting. The specific process of historical fitting is as follows: The first step is to determine the objective of the history fitting process; The second step is to select a historical fitting method based on the historical fitting target, company resources, fitting period, and data reliability. The third step is to determine the historical production data to be fitted and the criteria for successful fitting. Step 4: Determine the adjustable reservoir data and reliable range during the historical fitting process; Step 5: Run the simulation model using the most reliable input data; Step 6: Compare the historical fitting results with the production data selected in Step 3; Step 7: Within a reliable range, vary the reservoir data selected in Step 4; Step 8: Repeat steps 5 through 7 until the fitting criteria in step 3 are met, and obtain the verification results.

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