A method for predicting the production decline rate of a low-permeability oil reservoir
By integrating multiple parameters and using a comprehensive decline coefficient to predict the production decline rate of low-permeability reservoirs, the problem of insufficient prediction complexity and accuracy in existing technologies is solved, and rapid and accurate production prediction is achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- SHAANXI YANCHANG PETROLEUM GRP
- Filing Date
- 2026-03-12
- Publication Date
- 2026-07-31
AI Technical Summary
Existing technologies cannot efficiently, accurately, and mechanistically predict the production decline rate of low-permeability reservoirs, and existing methods are complex to calculate, costly, or have poor versatility.
A multi-parameter fusion-based approach is adopted to construct a comprehensive decline coefficient by obtaining the comprehensive influence factors of the target block and similar blocks. Combined with static geological parameters, dynamic development parameters, and preset deployment parameters, the annual decline rate of production is predicted using a formula.
It enables rapid and accurate prediction of production decline rate in low-permeability reservoirs, providing quantitative basis for optimizing development schemes, with an error of less than 5%.
Smart Images
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Abstract
Description
Technical Field
[0001] This invention belongs to the field of oilfield development technology, specifically relating to a method for predicting the production decline rate of low-permeability oil reservoirs. Background Technology
[0002] Low-permeability reservoirs (generally referring to reservoirs with air permeability less than 50 mD) are an important type of oil and gas resource in my country, accounting for over 60% of total reserves. Low-permeability reservoirs are characterized by complex pore structures, high flow resistance, low natural productivity, and rapid production decline. Accurately predicting the production decline rate of low-permeability reservoirs is crucial for developing reasonable development adjustment plans, optimizing production deployment, and improving recovery rates. Currently, the main methods for predicting reservoir production decline rates include the following: 1. Production dynamic methods: such as the Arps decline curve method and the water drive curve method. These methods are based on production data fitting, which is simple and easy to use, but requires a sufficiently long production history dynamic data, has high requirements for production data, and fails to consider the impact of changes in reservoir geological characteristics and development conditions. 2. Numerical simulation method: This method involves numerical simulation of the reservoir by establishing a detailed geological model. Theoretically, this method has high accuracy, but the modeling process is complex, requiring a large amount of geological, well logging, and core data, resulting in high computational costs and a large workload, making it difficult to meet the needs of rapid evaluation and real-time optimization. 3. Statistical analysis method: This method calculates the decline rate by establishing a statistical relationship between the decline rate and one or a few parameters (such as permeability or well density). The physical meaning of the model in this method is not clear enough, and its universality is poor; different reservoirs require the establishment of new statistical relationships.
[0003] Therefore, existing technologies have the drawback of being unable to efficiently, accurately, and mechanistically characterize the decline rate of low-permeability reservoirs. There is an urgent need for a decline rate prediction method that can integrate multi-parameter information, has clear physical meaning, and is fast and easy to calculate. Summary of the Invention
[0004] The present invention aims to address the above-mentioned problems by providing a method for predicting the production decline rate of low-permeability reservoirs based on multi-parameter fusion.
[0005] The technical solution of this invention is as follows: A method for predicting the production decline rate of low-permeability oil reservoirs is as follows: Obtain the comprehensive impact factor of similar blocks in the target block; the comprehensive impact factor of similar blocks is the sum of three items: reservoir quality and water content impact item, injection-production balance item, and energy well network interference item; The comprehensive decline coefficient is constructed by dividing the sum of the products of the comprehensive impact factors of all similar blocks and the corresponding actual decline rates by the sum of the squares of the comprehensive impact factors of all similar blocks. The formula for calculating the annual decline rate of predicted production is constructed by multiplying the sum of the reservoir quality and water content factors, the injection-production balance factor, and the energy well network interference factor of the target block with the comprehensive decline coefficient, and then the annual decline rate of predicted production is calculated.
[0006] A method for predicting the production decline rate of low-permeability oil reservoirs is as follows: Substitute static geological parameters, dynamic geological parameters, and preset deployment parameters into the following formula to calculate the predicted annual decline rate of production. ; (1) In the formula: This is the overall decreasing coefficient; The baseline value for the penetration rate of the target block; The average penetration rate of the target block; The average porosity of the target block; The average oil saturation of the target block; The overall moisture content of the target block; The injection-production ratio for the target block stage; The average formation pressure of the target block; The original formation pressure of the target block; The target block well density; The base well density for the target block; Among them, the comprehensive decreasing coefficient The specific solution process is as follows: (2) (3) In the formula: This refers to the sequence number of blocks of the same type; This represents the maximum number of blocks of the same type. For the first Comprehensive impact factor of similar blocks; For the first The actual decline rate of similar blocks; For the first Benchmark penetration rates for similar blocks; For the first Average penetration rate of similar blocks; For the first Average porosity of similar blocks; For the first Average oil saturation of similar blocks; No. Overall moisture content of similar blocks; For the first The injection-production ratio in the same type of block; For the first Average formation pressure in similar blocks; For the first The original formation pressure of similar blocks; For the first Well density in similar blocks; For the first Basic well density in similar blocks.
[0007] Formula (1) consists of three terms with clear physical meaning.
[0008] 1. Sub-items for the influence of reservoir quality and water content; molecular As the core term, the key controlling factor for the decline in low-permeability reservoirs is permeability, and the nonlinear effect of permeability on decline is characterized by logarithmic form. denominator Porosity and oil saturation serve as indicators of the degree of reservoir accumulation and enrichment, and their product simply represents the quality of the reservoir's material basis. multiplier Linear characterization of the exacerbating effect of rising water content on the decline; Overall significance: This item comprehensively reflects the inherent geological endowment of the oil reservoir ( , , ) and the development status after the event ( The combined effect of these factors on the projected annual rate of decline in output.
[0009] 2. Injection-Protection Balance Item: ; Utilizing the deviation of the injection-production ratio from the equilibrium state in the stage ( The degree of underpayment, as a linear additional contribution to the decline rate, is considered. ) or over-bet ( All of these will exacerbate the decline and increase the decline rate.
[0010] 3. Energy and well pattern interference: ; use The effect of maintaining pressure levels reflects the accelerating effect of energy decay on the rate of decline; It indicates the density of the well network relative to a reasonable well network, reflecting the degree of interference between wells.
[0011] The average penetration rate of the target block Passing the exam Average porosity of similar blocks It is calculated from acoustic transit time or density and neutron logging curves.
[0012] The average penetration rate of the target block Passing the exam Average penetration rate of similar blocks The results were obtained by fitting the porosity-permeability relationship through core analysis.
[0013] The average oil saturation of the target block Passing the exam Average oil saturation of similar blocks It was calculated using Archie's formula.
[0014] The overall moisture content of the target block Target Block Phase Injection-to-Production Ratio , No. Overall moisture content of similar blocks Passing the exam Phase injection-production ratio of similar blocks Obtained through production reports and water injection reports.
[0015] The average formation pressure of the target block Passing the exam Average formation pressure in similar blocks This was obtained through well testing.
[0016] The target block well network density =Total number of wells in the target block / Oil-bearing area of the target block; Well density of similar blocks = Total number of wells in the same type of block / Oil-bearing area in the same type of block.
[0017] The target block penetration benchmark value Passing the exam Penetration benchmark value of similar blocks The optimal permeability level for the region is selected, with a range of 10-30 mD.
[0018] For low-permeability reservoirs, basic well pattern density , No. Basic well density of similar blocks The value range is 4~10 m / km 2 .
[0019] Among them, the same type of block refers to the same type of block in the reservoir where the target oil layer is located or the same type of block in other oil reservoirs.
[0020] The technical effects of this invention are as follows: This invention application systematically integrates data from three dimensions: static geological parameters, dynamic development parameters, and preset deployment parameters of oil reservoirs, to achieve rapid and accurate prediction of the decline rate of low-permeability oil reservoirs, providing a quantitative basis for optimizing development schemes. Detailed Implementation
[0021] A method for predicting the production decline rate of low-permeability oil reservoirs is described below.
[0022] Step 1: Obtain the following parameters for the target block: Static geological parameters: average permeability of the target block Average porosity of the target block and the average oil saturation of the target block ; Dynamic development parameters: Overall moisture content of the target block Target Block Phase Injection-to-Production Ratio Average formation pressure in the target block Original formation pressure in the target block and target block well density ; Preset deployment parameters: Target block penetration benchmark value and the density of basic well networks in the target block .
[0023] Step 2: Collect historical parameter data and corresponding actual decline rates of the reservoir where the target block is located or similar blocks. Then, the comprehensive impact factor of each similar block is calculated according to formula (3). Then, the overall decreasing coefficient can be calculated using formula (2). Substitute the values into formula (1) to calculate the predicted annual decline rate of output. .
[0024] Specific experimental cases Taking a low-permeability block in the Yanchang Oilfield as the target block, the actual production decline rate of this target block is 8.3% / year. The method proposed in this invention is used to predict the production decline rate of this target block.
[0025] Step 1: Obtain the following parameters for the target block: Average penetration rate of target blocks Average porosity of the target block Average oil saturation of the target block The overall moisture content of the target block Target block phase injection-to-production ratio Average formation pressure in the target block With the original formation pressure of the target block The ratio is 0.9, and the well network density of the target block is... ; Based on regional geological characteristics and economic evaluation results, the pre-set deployment parameters are as follows: the benchmark value of permeability in the target block. Target block basic well network density .
[0026] Step 2: Collect historical data from four similar blocks, and calculate the comprehensive impact factor of each similar block according to formula (3). As shown in Table 1 below; Table 1 Historical data of 4 similar blocks ; The overall decreasing coefficient is obtained by solving formula (2). : ; The predicted annual decline rate of output can be calculated using formula (1). : .
[0027] Error analysis: The predicted annual decline rate of output calculated using this invention The estimated annual decline rate is 8.11%, while the actual decline rate for this block is 8.3% per year; the calculated absolute error is... relative error The prediction accuracy meets the requirements of industrial applications (error < 5%).
Claims
1. A method for predicting the production decline rate of low-permeability oil reservoirs, characterized in that, The method is as follows: Obtain the comprehensive impact factor of similar blocks in the target block; the comprehensive impact factor of similar blocks is the sum of three items: reservoir quality and water content impact item, injection-production balance item, and energy well network interference item; The comprehensive decline coefficient is constructed by dividing the sum of the products of the comprehensive impact factors of all similar blocks and the corresponding actual decline rates by the sum of the squares of the comprehensive impact factors of all similar blocks. The formula for calculating the annual decline rate of predicted production is constructed by multiplying the sum of the reservoir quality and water content factors, the injection-production balance factor, and the energy well network interference factor of the target block with the comprehensive decline coefficient, and then the annual decline rate of predicted production is calculated.
2. The method for predicting the production decline rate of low-permeability oil reservoirs according to claim 1, characterized in that, The method is as follows: Substitute static geological parameters, dynamic geological parameters, and preset deployment parameters into the following formula to calculate the predicted annual decline rate of production. ; （1） In the formula: This is the overall decreasing coefficient; The baseline value for the penetration rate of the target block; The average penetration rate of the target block; The average porosity of the target block; The average oil saturation of the target block; The overall moisture content of the target block; The injection-production ratio for the target block stage; The average formation pressure of the target block; The original formation pressure of the target block; The target block well density; The base well density for the target block; Among them, the comprehensive decreasing coefficient The specific solution process is as follows: （2） （3） In the formula: This refers to the sequence number of blocks of the same type; This represents the maximum number of blocks of the same type. For the first The comprehensive impact factor of similar blocks; For the first The actual decay rate of similar blocks; For the first Benchmark penetration rates for similar blocks; For the first Average penetration rate of similar blocks; For the first Average porosity of similar blocks; For the first Average oil saturation of similar blocks; No. Overall moisture content of similar blocks; For the first The injection-production ratio at different stages for similar blocks; For the first Average formation pressure in similar blocks; For the first The original formation pressure of similar blocks; For the first Well density in similar blocks; For the first Basic well density in similar blocks.
3. The method for predicting the production decline rate of low-permeability reservoirs according to claim 2, characterized in that, The average penetration rate of the target block Passing the exam Average porosity of similar blocks It is calculated from acoustic transit time or density and neutron logging curves.
4. The method for predicting the production decline rate of low-permeability oil reservoirs according to claim 2, characterized in that, The average penetration rate of the target block Passing the exam Average penetration rate of similar blocks The results were obtained by fitting the porosity-permeability relationship through core analysis.
5. The method for predicting the production decline rate of low-permeability oil reservoirs according to claim 2, characterized in that, The average oil saturation of the target block Passing the exam Average oil saturation of similar blocks It was calculated using Archie's formula.
6. The method for predicting the production decline rate of low-permeability oil reservoirs according to claim 2, characterized in that, The overall moisture content of the target block Target Block Phase Injection-to-Production Ratio , No. Overall moisture content of similar blocks Passing the exam Phase injection-production ratio of similar blocks Obtained through production reports and water injection reports.
7. The method for predicting the production decline rate of low-permeability oil reservoirs according to claim 2, characterized in that, The average formation pressure of the target block Passing the exam Average formation pressure in similar blocks This was obtained through well testing.
8. The method for predicting the production decline rate of low-permeability oil reservoirs according to claim 1, characterized in that, The target block well network density =Total number of wells in the target block / Oil-bearing area of the target block; Well density of similar blocks = Total number of wells in the same type of block / Oil-bearing area in the same type of block.
9. The method for predicting the production decline rate of low-permeability oil reservoirs according to claim 2, characterized in that, The target block penetration benchmark value Passing the exam Penetration benchmark value of similar blocks The optimal permeability level for the region is selected, with a range of 10-30 mD.
10. The method for predicting the production decline rate of low-permeability reservoirs according to claim 2, characterized in that, For low-permeability reservoirs, basic well pattern density , No. Basic well density of similar blocks The value range is 4~10 m / km 2 .