A method for establishing a benefit development chart for low-abundance low-permeability tight sandstone gas reservoirs and a benefit development method

Abstract

This invention discloses a method for establishing a development map and a development method for low-abundance, low-permeability tight sandstone gas reservoirs. The map establishment method includes: S1, selecting typical well areas and using multi-factor sensitivity analysis to determine the main controlling factors affecting recovery rate; S2, using dynamic and static methods to establish the relationship between net profit and recoverable reserves for different well types under different economic policies; S3, using typical well areas to predict the recoverable reserves of gas wells under different recovery rate controlling factors, and combining the relationship between net profit and recoverable reserves to obtain the relationship between different controlling factors and net profit, i.e., the gas reservoir development map. A dynamically changing development potential evaluation model is established by combining the map and the gas reservoir numerical model. This model can quantitatively predict and evaluate the development potential of gas reservoirs from production to abandonment at any time, in any well area, and in any gas layer under different economic and technological policies, realizing real-time dynamic evaluation of the development potential of gas reservoirs.

Description

Technical Field

[0001] This invention relates to the field of gas reservoir development technology, and in particular to a method for establishing a map and developing a gas reservoir with low abundance and low permeability in tight sandstone. Background Technology

[0002] Low-permeability tight sandstone gas resources are abundant, mainly distributed in several basins including the Ordos, Sichuan, Songliao, and Bohai Bay basins. The proven reserves of low-permeability tight sandstone gas reservoirs in the Sichuan Basin exceed 1.2 × 10¹² m³. 3 It has enormous development potential. However, the poor physical properties and low reserve abundance of low-permeability tight sandstone gas reservoirs make economic development difficult. In particular, as the gas reservoir enters the later stages of development, all high-quality reserves have been utilized, and the remaining reserves are distributed in the Class II and III reservoirs with poor reservoir quality. The remaining reserves are low in abundance, making economic development difficult.

[0003] In the later stages of development of low-permeability tight sandstone gas reservoirs, infill drilling and adjustment are the main focus, and the selection of infill drilling and adjustment zones directly affects development efficiency. Currently, numerical simulations are commonly used to describe the distribution of remaining gas in the reservoir, using original formation pressure, reservoir properties, and gas content to determine infill drilling and adjustment zones. However, this method has three shortcomings: First, the evaluation indicators for infill drilling and adjustment potential zones need further optimization. Currently, the main evaluation indicator is formation pressure, combined with reservoir properties or gas saturation parameters. Multi-parameter evaluation has certain uncertainties, and its accuracy needs improvement compared to evaluation using a single indicator. Second, the impact of formation pressure decline on adjustment potential is not considered. Early infill drilling and adjustment requires maintaining the original formation pressure, but recent field tests and multi-method demonstrations have found that the inter-well disturbance for achieving the highest recovery rate in low-permeability tight sandstone gas reservoirs is about 30%, and the inter-well disturbance for achieving the best economic benefits is about 85%. Whether from the perspective of recovery rate or economic benefits, infill drilling and adjustment can be carried out in areas with declining formation pressure. However, there are almost no reports on research related to formation pressure changes in the evaluation of infill drilling and adjustment potential zones. Third, in addition to the resource quality and scale of the gas reservoir itself, the development benefits of low-permeability tight sandstone gas reservoirs are also closely related to development costs, gas prices, and fiscal policies. Even when the development plan is optimized based on economic limit production in the gas reservoir engineering scheme, the separate evaluation of technology and economics means that the gas reservoir development may not achieve the optimal economic benefits.

[0004] Gas reservoir recovery rate is a crucial indicator for evaluating gas field development effectiveness and making development decisions. The recovery rate of low-permeability tight sandstone gas reservoirs is mainly influenced by two factors: geology and development. Development factors such as well network, well spacing, well type, rational production allocation, and gas production rate can be optimized through scheme design. Recovery rate influencing factor analysis, with potential evaluation as its core, mainly targets geological factors inherent to the gas reservoir itself, such as reservoir properties, gas content, and effective sand body thickness. Numerical simulation methods are often used for single-factor influence analysis to determine the main control factors of recovery rate. For example, patent CN114427432A discloses a method for determining the remaining gas development potential of a gas reservoir, including S1: establishing a gas reservoir numerical simulation model; S2: determining the main factors for gas development in the current static and dynamic parameter fields of the gas reservoir; and S4: establishing the recoverable reserves of a single well and the main control factors of remaining gas. The patent, in determining the main controlling factors of residual gas, establishes a correlation chart between geological parameters of the residual gas area and the economically recoverable reserves of a single well. It uses correlation coefficients to determine whether a factor is a major factor affecting the development potential of residual gas. However, this method has two problems: First, using recoverable reserves as the evaluation index for the main controlling factor of residual gas potential, the multiple regression does not consider the correlation between reservoir properties such as porosity, permeability, gas content, and effective thickness. Secondly, porosity, gas content, and effective thickness affect reserves; higher porosity, gas content, and effective thickness result in higher reserves and recoverable reserves, but reservoir recovery rate and reserves are not positively correlated, so recoverable reserves cannot be used as an evaluation index for reservoir potential. Second, it does not consider the impact of formation pressure decline on reservoir potential. In the early stages of development, infill drilling in gas reservoirs requires maintaining the original formation pressure. However, recent field tests and multi-method demonstrations have revealed that inter-well interference is approximately 30% when tight sandstone gas reservoirs achieve maximum recovery, and approximately 85% for optimal economic benefits. Even with reduced formation pressure, infill wells can still achieve high economic returns. Therefore, formation pressure variations must be considered when evaluating the development potential of gas reservoirs. Summary of the Invention

[0005] The purpose of this invention is to overcome the above-mentioned deficiencies in the prior art and to provide a method for establishing a map and developing a gas reservoir with low abundance and low permeability.

[0006] To achieve the above-mentioned objectives, the present invention provides the following technical solution:

[0007] A method for establishing a map for the efficient development of low-abundance, low-permeability tight sandstone gas reservoirs includes the following steps:

[0008] S1. Select typical well areas and determine the main controlling factors affecting the recovery rate based on the range of changes in the static geological characteristics of the well areas using multi-factor sensitivity analysis.

[0009] S2. Establish the relationship between net profit and recoverable reserves for different well types under different economic policies using dynamic and static methods;

[0010] S3. Using typical well areas, predict the recoverable reserves of gas wells under different recovery rate control factors. Combine the relationship between net profit and recoverable reserves to obtain the relationship between different control factors and net profit, i.e., the gas reservoir benefit development chart.

[0011] In the technical solution of this invention, multi-factor and multi-method sensitivity analysis is used to comprehensively analyze typical well areas to determine the main controlling factors of recovery rate in low-permeability tight sandstone gas reservoirs. Simultaneously, based on different investment entities and payback periods, either dynamic or static methods are selected to establish the relationship between net profit and recoverable reserves. By combining the relationship between net profit and recoverable reserves, the relationship between different main controlling factors and net profit is obtained, enabling economic evaluation of the gas reservoir. Steps S1 and S2 are not sequential.

[0012] Furthermore, when selecting typical well areas, it is necessary to analyze typical well areas from different reserve zones, including Class I, Class II, and Class III reserve zones. Even further, the criteria for selecting typical well areas are: the recoverable reserves of the gas well are greater than 60%, and the gas well has entered a low-pressure, low-production stage. Low pressure refers to the wellhead pressure being less than 2 MPa, and low production refers to the daily gas production of the gas well being less than 1000 cubic meters per day.

[0013] Furthermore, when conducting multi-factor sensitivity analysis, the geological factors affecting the recovery rate include porosity, permeability, effective thickness, water saturation, and formation pressure. The influence of geological factors on the recovery rate is calculated by simultaneously varying multiple parameters.

[0014] Furthermore, the main controlling factors of recovery rate are formation pressure and reserve abundance, with reserve abundance comprehensively representing porosity, effective thickness, and water saturation.

[0015] Further, in step S3, based on the relationship between different controlling factors and net profit, the minimum reserve abundance for profitable development under different formation pressures is obtained. Specifically, based on the relationship between different formation pressures, different reserve abundances, and net profit, the net profit is set to 0, thus obtaining the relationship between different formation pressures and the minimum reserve abundance. When the net profit is 0, it is the critical point for profitable development; the corresponding reserve abundance is the minimum reserve abundance for profitable development under the current formation pressure. Areas with remaining reserve abundance greater than the minimum reserve abundance for profitable development under the corresponding formation pressure are considered potential areas for profitable development.

[0016] Furthermore, different economic policies include different internal rates of return (IRRs) and different gas prices, with IRRs ranging from 0% to 12% and gas prices ranging from 1200 to 1600 yuan / 10. 3m, the relationship between net profit and recoverable reserves under different economic policies established using the static method is as follows:

[0017] N p =G p ×[P t (1-T r -T i )-C t ]

[0018] The relationship between net profit and recoverable reserves under different economic policies, established using the dynamic method, is as follows:

[0019] N p =(G p -E lc )×P t (1-T r -T i )-C r

[0020] In the formula N p Net profit, in yuan; G p To accumulate gas production, 10 8 m 3 ;P t For oil and gas prices, in yuan / 10 3 m 3 ;T r Resource tax, %; T i For income tax, %; C t Total production cost, in yuan / 10 3 m 3 E lc For the economically recoverable reserves, 10 8 m 3 C r Total operating cost, in yuan / 10 3 m 3 .

[0021] Furthermore, the economically recoverable reserves of a single well are calculated using the cash flow method.

[0022] Another aspect of the present invention provides a method for the later-stage development of low-abundance, low-permeability tight sandstone gas reservoirs, comprising the following steps:

[0023] Step 1: Obtain dynamic monitoring data of the target gas reservoir, and establish a numerical model of the gas reservoir based on the detailed three-dimensional model of the gas reservoir and constrained by the dynamic monitoring data;

[0024] Step 2: Based on the gas reservoir numerical model, obtain the numerical distribution of different main controlling factors of the target gas reservoir. Combined with the above gas reservoir benefit development map, establish a benefit development potential evaluation model to obtain the benefit development potential of any gas layer of the target gas reservoir at any time from production to abandonment, and divide it into potential areas and no-potential areas.

[0025] Step 3: Establish development technology strategies for different reserve areas, and deploy well locations according to the potential areas identified in Step 2 to achieve the later-stage benefit development of low-abundance, low-permeability tight sandstone gas reservoirs.

[0026] In this invention, the potential zone refers to the area where net profit is greater than 0, and the no-potential zone refers to the area where net profit is less than 0.

[0027] Furthermore, the detailed three-dimensional model of the gas reservoir is established based on the reservoir's formation parameters and production parameters.

[0028] Furthermore, the steps for establishing a gas reservoir numerical model, constrained by gas reservoir dynamic monitoring data, include: predicting gas reservoir production data using the refined three-dimensional model, comparing the predicted production data with the dynamic monitoring data, and calculating the fitting rate of the reservoir parameters. If the fitting rate is >90%, the prediction results of the gas reservoir numerical model are considered to match the actual production data; otherwise, the refined three-dimensional model is re-established by modifying the permeability and conductivity used in establishing the refined three-dimensional model. Further, the gas reservoir parameters include reserves, single-well production, and single-well headwater pressure.

[0029] Furthermore, the potential area is subdivided into six zones: low reserve abundance with high formation pressure potential zone, low reserve abundance with medium to high formation pressure potential zone, medium-low reserve abundance with medium to high formation pressure potential zone, medium reserve abundance with medium formation pressure potential zone, medium-high reserve abundance with medium formation pressure potential zone, and high reserve abundance with low formation pressure potential zone. In step three, well locations are deployed according to the different potentials of each sub-zone.

[0030] Furthermore, developing technical strategies for different reserve areas includes well type selection, horizontal well optimization, selection of reasonable well spacing, and reasonable production output.

[0031] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0032] 1. This invention, by screening the factors affecting oil recovery, identifies and establishes the relationship between each key factor and net profit, resulting in a gas reservoir benefit development chart. This invention clarifies an internal rate of return of 0%–12% and a gas price of 1200–1600 yuan / 10 3 m 3The impact of 40%–100% original formation pressure on the minimum reserve abundance for profitable development was investigated, and a series of charts for the minimum reserve abundance for profitable development were established for different well types. Combining these charts with a gas reservoir numerical model, a dynamically changing evaluation model for profitable development potential was established. This model can quantitatively predict and evaluate the profitable development potential of gas reservoirs at any time, in any well area, and in any gas layer under different economic and technological policies, from production to abandonment. This invention utilizes a dynamic model for evaluating profitable development potential established using numerical models and integrated economic and technological techniques. This model enables real-time dynamic evaluation of low-abundance, low-permeability tight sandstone gas reservoirs, ensuring economic benefits and providing a strong basis for improving recovery rates and profitable development of gas reservoirs in the later stages of development.

[0033] 2. The method of this invention is applicable to further enhancing the recovery rate in the later stages of development of low-abundance, low-permeability tight sandstone gas reservoirs, ensuring the efficient development of these reservoirs. It plays a crucial role in the efficient development and enhanced recovery of low-abundance, low-permeability tight sandstone gas reservoirs. my country has a wide distribution area and large reserves of low-permeability tight sandstone gas reservoirs, but efficient development is challenging, and recovery rates are generally low. Therefore, this method has broad application prospects. Attached image description:

[0034] Figure 1 A flowchart illustrating the method for establishing a map for the efficient development of low-abundance, low-permeability tight sandstone gas reservoirs;

[0035] Figure 2 A bar chart showing the factors affecting oil recovery and their magnitude.

[0036] Figure 3 A graph showing the relationship between different internal rates of return (IRR) and economically recoverable reserves.

[0037] Figure 4 A graph showing the relationship between well depth and economically recoverable reserves at different gas prices;

[0038] Figure 5 A graph showing the relationship between reserves abundance and net profit under different formation pressures;

[0039] Figure 6 A map showing the reserve abundance of different well types under varying formation pressures;

[0040] Figure 7 A map showing the development of reserves and abundance for vertical wells under different formation pressures with varying internal rates of return;

[0041] Figure 8 A map showing the efficiency of developing reserves and abundance of vertical wells under different formation pressures at different gas prices;

[0042] Figure 9 A schematic diagram of the numerical model of the XX gas reservoir;

[0043] Figure 10A schematic diagram of the benefit development evaluation model for the XX gas reservoir;

[0044] Figure 11 A graph showing the relationship between reserve abundance and net profit for different well types;

[0045] Figure 12 This graph shows the relationship between reserve abundance and profit for different well types under different formation pressure conditions. Detailed Implementation

[0046] The present invention will be further described in detail below with reference to experimental examples and specific embodiments. However, this should not be construed as limiting the scope of the above-mentioned subject matter of the present invention to the following embodiments; all technologies implemented based on the content of the present invention fall within the scope of the present invention.

[0047] Example 1

[0048] like Figure 1 As shown in the figure, this embodiment provides a method for establishing a map for the efficient development of low-abundance, low-permeability tight sandstone gas reservoirs, including the following steps:

[0049] S1. Select typical well areas and determine the main controlling factors affecting the recovery rate based on the range of changes in the static geological characteristics of the well areas using multi-factor sensitivity analysis.

[0050] S2. Establish the relationship between net profit and recoverable reserves for different well types under different economic policies using dynamic and static methods;

[0051] S3. Using typical well areas, predict the recoverable reserves of gas wells under different recovery rate control factors. Combine the relationship between net profit and recoverable reserves to obtain the relationship between different control factors and net profit, i.e., the gas reservoir benefit development chart.

[0052] The XX gas reservoir is located on the Xinchang tectonic uplift zone, trending northeast, in the central section of the western Sichuan depression within the Sichuan Basin, on the Upper Yangtze Platform. It is a gently sloping, nose-shaped structure extending eastward from the Xiaoquan anticline. The XX gas reservoir is buried at a depth of 600-1700 meters, with a stratigraphic thickness of approximately 1100 meters. From top to bottom, it is divided into three gas reservoirs: JP1, JP2, and JP3. These reservoirs exhibit significant differences in physical properties. JP1 has an average porosity of 15.02%, an average permeability of 4.89 mD, an average geothermal gradient of 1.89℃ / 100m, and an average pressure coefficient of 1.34. JP2 has an average porosity of 11.83%, an average permeability of 1.38 mD, an average geothermal gradient of 1.93℃ / 100m, and an average pressure coefficient of 1.49. JP3 has an average porosity of 10.32%, an average permeability of 0.43 mD, an average geothermal gradient of 2.30℃ / 100m, and an average pressure coefficient of 1.65. The XX gas reservoir is a low-permeability to near-tight porous, structural-lithological high-pressure elastic gas-driven dry gas reservoir without obvious edge or bottom water. It is characterized by narrow channels, thin sand bodies, low-permeability and tight reservoir, low production capacity, and low reserve abundance. Since its discovery in 1992, the reservoir has gone through a trial production and production increase phase (1992-1995), a stable production phase (1996-2004), and a declining production phase (2005-present). The XX gas reservoir is developed using a non-uniform well pattern of single-layer vertical wells and multiple multi-layer commingled vertical wells; single-well production capacity is extremely low, with an average single-well production capacity of only 3.83 × 10⁻⁶. 4 m 3 / d; the reservoir has strong seepage capacity and a large venting radius, mainly distributed in the range of 280-450m; the dynamic control reserves are low, with an average dynamic reserve of only 0.31×10 4 m 8 .

[0053] The study of the main controlling factors affecting recovery rate selected typical well areas from different reserve zones. These typical well areas were those actually developed, each containing multiple gas wells, possibly 3-5 or 7-8. The XX gas reservoir has complex geological conditions and extremely strong heterogeneity between and within river channels. This reserve classification evaluation, based on full consideration of differences in reservoir properties and gas-bearing capacity, introduced reserve abundance as a standard for classifying reserve types. Different reserve zones were categorized into Class I, Class II, and Class III. The criteria for selecting typical well areas were: recoverable reserves greater than 60%, and the well entering a low-pressure, low-production stage. Low pressure refers to a wellhead pressure less than 2 MPa, and low production refers to a daily gas production of less than 1000 cubic meters per day.

[0054] Multifactor sensitivity analysis was used to design combinations of geological factors such as porosity, permeability, effective thickness, water saturation, and formation pressure. The Mixed Factorial sensitivity analysis was employed to calculate the impact on recovery rate. For example, changing the formation pressure data would cause changes in other geological factors related to formation pressure, such as permeability and water saturation. Through simultaneous changes in multiple parameters, the numerical model generated up to 600 sets of parameters, comprehensively analyzing their impact on recovery rate and calculating the magnitude of the impact. The results are shown in Table 1. (Based on the data, plotted...) Figure 2 .

[0055] Table 1. Impact of Recovery Rate on Typical Well Areas in Different Reserve Zones

[0056]

[0057]

[0058] According to the data in Table 1, the recovery rate of the XX gas reservoir is most significantly affected by formation pressure in all different reservoir areas. The recovery rate in Class I reservoirs is most affected by formation pressure, reaching 43.5%. As reservoir properties deteriorate, the impact of formation pressure on the recovery rate weakens, but it remains the primary influencing factor. In Class III reservoirs, formation pressure still affects the recovery rate by 11.7%. The next most significant factors influencing the recovery rate are water saturation, permeability, and effective thickness, affecting the recovery rate by 5-13%. The worse the reservoir quality, the greater the impact. The recovery rate in Class I reservoirs is affected by the combined influence of these three factors at 21.1%, while the impact increases to 29.9% in Class III reservoirs. Porosity has the least impact on the recovery rate of the XX gas reservoir, consistently less than 2%, and can be considered negligible. Therefore, the main controlling factors affecting the recovery rate of the XX gas reservoir are formation pressure and the abundance of reserves, which comprehensively characterizes porosity, effective thickness, and water saturation.

[0059] When conducting economic evaluations, either dynamic or static methods are selected based on the investment entity and payback period. The relationship between net profit and recoverable reserves (i.e., cumulative gas production and economically recoverable reserves) under different economic evaluation methods is established. The relationship between net profit and recoverable reserves established using the static method is as follows:

[0060] N p =G p ×[P t (1-T r -T i )-C t (1)

[0061] The relationship between net profit and recoverable reserves established using the dynamic method is as follows:

[0062] N p =(G p -Elc )×P t (1-T r -T i )-C r (2)

[0063] In the formula N p Net profit, in yuan; G p To accumulate gas production, 10 8 m 3 ;P t For oil and gas prices, in yuan / 10 3 m 3 ;T r Resource tax, %; T i For income tax, %; C t Total production cost, in yuan / 10 3 m 3 E lc For the economically recoverable reserves, 10 8 m 3 C r Total operating cost, in yuan / 10 3 m 3 .

[0064] Currently, enterprises commonly use the internal rate of return (IRR) and net present value (NPV) to evaluate the economic viability of gas reservoir development. A gas reservoir with an after-tax IRR greater than the industry benchmark rate of return (8% pre-tax) and an after-tax NPV greater than zero is considered a profitable development; the higher the after-tax NPV, the higher the economic benefit. The IRR is related to national preferential policies. An IRR of 0 indicates the gas reservoir development is at the break-even point; the investment return can withstand currency devaluation and inflation, but no economic benefit is achieved. The NPV is mainly affected by gas prices, investment, production costs, and taxes. Evaluating the profitability of a specific gas reservoir primarily considers IRR and gas price fluctuations; a decrease in IRR or an increase in gas prices can increase development potential. In this example, under the condition of meeting the economic limit production of a single well, the economic limit recoverable reserves of a single well are calculated using the cash flow method, based on the economic boundary of a single well, with a construction period of 1 year, a stable production period of 2 years, a comprehensive decline rate of 16%, and an evaluation period of 15 years, predicting an IRR of 0%–12% and a gas price of 1200–1600 yuan / 10. 3 At m, the economically recoverable reserves of different well types, including vertical and horizontal wells, at different depths, such as Figures 3-4 As shown.

[0065] Using typical well areas, the recoverable reserves of gas wells under different reserve abundances and formation pressures are predicted. Figures 3-4 Formulas (1) and (2) yield a series of relationship diagrams between net profit and different formation pressures, different reserve abundances, and different internal rates of return and different gas prices. Figure 5 Only the internal rate of return of 8% and the gas price of 1404 yuan / 10 were shown. 3 m 3 The graph shows the relationship between reserve abundance and net profit for vertical wells under different formation pressures. It indicates that regardless of formation pressure, higher reserve abundance leads to greater net profit from well deployment. Based on the relationship between different controlling factors and net profit, the minimum reserve abundance for profitable development under different formation pressures is obtained. Specifically, the relationship between net profit and different formation pressures is calculated by setting the net profit to 0, thus obtaining the relationship between different formation pressures and the minimum reserve abundance. A net profit of 0 represents the critical point for profitable development; the corresponding reserve abundance is the minimum reserve abundance for profitable development under the current formation pressure. Areas with remaining reserve abundance greater than the minimum reserve abundance for profitable development under the corresponding formation pressure represent potential areas for profitable development.

[0066] Based on the minimum reserve abundance method, an internal rate of return of 0%–12% and a gas price of 1200–1600 yuan / 10 were established under conditions of 40%–100% original formation pressure. 3 m 3 A series of charts showing the minimum reserve abundance for efficient development of different well types, such as... Figures 6-8 As shown.

[0067] Figure 6 Minimum reserve abundance maps were developed for the profitability of vertical and horizontal wells under different formation pressures. This was based on an internal rate of return of 8% and a gas price of 1404 yuan / 10... 3 m 3 When the formation pressure decreases, the reserve abundance for efficient development of both vertical and horizontal wells initially decreases slowly, then rapidly decreases when the formation pressure drops to 70% of the original formation pressure, exhibiting an exponential trend. When the formation pressure is greater than 70% of the original formation pressure, the minimum reserve abundance for efficient development is almost identical across different well types, allowing for optimal selection based on well type profitability. When the formation pressure is less than 70% of the original formation pressure, the increase in minimum reserve abundance for efficient development of vertical wells is significantly greater than that of horizontal wells. For example, if the formation pressure is only 40% of the original formation pressure, the remaining reserves required for efficient development of vertical wells increase to 4.67 × 10⁻⁶. 8 m 3 / Km 2 This is approximately 1.7 times that of horizontal wells. Therefore, in areas where formation pressure is maintained to a high degree, the remaining reserves are greater than 0.44–0.65 × 10⁻⁶. 8 m 3 / Km 2 Both vertical and horizontal wells can be used for efficient development; in areas with low formation pressure, the remaining reserves required for horizontal well development are 0.79–2.7 × 10⁻⁶. 8 m 3 / Km 2Only 60% to 90% of the reserves can be effectively developed using vertical wells, making horizontal well development the preferred option.

[0068] Figure 7 This chart shows the minimum reserve abundance required for profitable development of vertical wells at different formation pressures, with an internal rate of return (IRR) ranging from 0% to 12%. Regardless of formation pressure, the remaining reserve abundance for profitable development of vertical wells increases with increasing IRR. The lower the formation pressure, the greater the increase in reserve abundance with increasing IRR; specifically, when the formation pressure is 60% lower than the original formation pressure, the minimum reserve abundance for profitable development increases by approximately 1.38 to 1.58 times as the IRR increases from 0% to 12%; when the formation pressure is 60% higher than the original formation pressure, the minimum reserve abundance for profitable development only increases by approximately 1.35 times. The minimum reserve abundance for profitable development of horizontal wells shows a similar pattern to that of vertical wells, but the impact of increasing IRR is less pronounced. As the IRR increases from 0% to 12%, the minimum reserve abundance required for profitable development of horizontal wells increases by approximately 1.30 to 1.35 times. When the formation pressure is 60% lower than the original formation pressure, the minimum reserve abundance for profitable development using horizontal wells is only 60% to 90% of that of vertical wells. Therefore, a lower internal rate of return is more beneficial to the later stages of gas reservoir development. Even if the formation pressure decreases, efficient development can still be achieved by using horizontal wells.

[0069] Figure 8 The gas price was displayed as 1200-1600 yuan / 10. 3 m 3 The minimum reserve abundance for efficient vertical well development corresponding to different formation pressures. Under the same formation pressure conditions, the reserve abundance for efficient vertical well development decreases with increasing gas price. When the gas price increases from 1400 yuan / 10... 3 m 3 Increased to 1600 yuan / 10 3 m 3 The required reserve abundance for profitable development decreases by approximately 10%. As formation pressure decreases, rising gas prices have a greater impact on the minimum reserve abundance required for profitable development; when formation pressure decreases from its original level to 50%, the required reserve abundance for profitable development decreases by approximately 20%; when formation pressure decreases to 40% of its original level, the required reserve abundance for profitable development decreases by approximately 25%. Horizontal wells exhibit the same variation pattern as vertical wells, but the difference is that the minimum reserve abundance required for profitable development of horizontal wells is always lower than that of vertical wells; the lower the formation pressure, the lower the required reserve abundance for profitable development compared to vertical wells.

[0070] Example 2

[0071] This embodiment provides a method for the later-stage development of low-abundance, low-permeability tight sandstone gas reservoirs, including the following steps:

[0072] Step 1: Obtain dynamic monitoring data of the target gas reservoir, and establish a numerical model of the gas reservoir based on the detailed three-dimensional model of the gas reservoir and constrained by the dynamic monitoring data;

[0073] Step 2: Based on the gas reservoir numerical model, obtain the numerical distribution of different main controlling factors of the target gas reservoir. Combined with the above gas reservoir benefit development map, establish a benefit development potential evaluation model to obtain the benefit development potential of any gas layer of the target gas reservoir at any time from production to abandonment, and divide it into potential areas and no-potential areas.

[0074] Step 3: Establish development technology strategies for different reserve areas, and deploy well locations according to the potential areas identified in Step 2 to achieve the later-stage benefit development of low-abundance, low-permeability tight sandstone gas reservoirs.

[0075] The accuracy of the numerical model of a gas reservoir determines the accuracy of the gas reservoir potential evaluation model. This embodiment uses the XX gas reservoir from Example 1. The detailed 3D model of the gas reservoir is established based on the reservoir's formation parameters and production parameters. Building upon the detailed 3D model established through multiple rounds of detailed reservoir description in the previous stage, a production history fitting is performed, constrained by dynamic monitoring data and based on production dynamics. In this embodiment, the XX gas reservoir is a low-permeability, near-tight, high-pressure, elastically driven dry gas reservoir with three phases of oil, gas, and water, but with low water and oil production. The detailed 3D model of the gas reservoir is suitable for establishment using the Eclipse 100 simulator, employing a black oil model. After coarsening, the detailed 3D model uses a uniform grid in the plane and an unequal-spacing grid in the vertical direction, the value of which depends on the effective thickness of the gas layer. The plane grid step size is 50m × 50m. The number of grids is 588 × 534 × 20 = 6,279,840.

[0076] Using data from 48 wells (193 times) of dynamic monitoring of static pressure and 255 wells (358 times) of pressure recovery as observation points, a 28-year production history fitting was performed on 431 wells to establish a gas reservoir numerical model. The steps included: predicting gas reservoir production data using the refined 3D model, comparing the predicted production data with the dynamic monitoring data, and calculating the fitting rate of the reservoir parameters. If the fitting rate was >90%, the prediction results of the gas reservoir numerical model were considered to match the actual production data; otherwise, the refined 3D model was re-established by modifying the permeability and conductivity used in establishing the refined 3D model. Furthermore, the gas reservoir parameters included reserves, single-well production, and single-well wellhead pressure. The established gas reservoir numerical model is as follows: Figure 9 As shown, the gas reservoir numerical model has a reserve fitting rate of 97.33%, a total area and single-well production fitting rate of 99.3%, and a single-well wellhead pressure fitting rate of 95%. These fitting rate data indicate a high fitting accuracy, demonstrating that the established gas reservoir numerical model is accurate, reliable, and has a small error range.

[0077] The unique timeliness and predictive ability of the gas reservoir numerical model can obtain the formation pressure distribution and remaining reserve abundance distribution map of any gas layer at any time from production to abandonment. Combined with the benefit development map in Example 1, a dynamic benefit development potential evaluation model is established to obtain the benefit development potential of any gas layer of the target gas reservoir at any time from production to abandonment, which is divided into potential areas and no-potential areas. The model can be changed according to changes in economic and technological policies and development time. Figure 10 This is a potential evaluation model for the XX gas reservoir under current economic conditions, with an internal rate of return of 8% and a gas price of 1404 yuan / 10. 3 m 3 The gas reservoir potential assessment model is based on data from December 2021. The potential area is subdivided into six zones: Zone 1 to Zone 6, which are respectively: low reserve abundance with high formation pressure potential zone, low reserve abundance with medium to high formation pressure potential zone, medium-low reserve abundance with medium to high formation pressure potential zone, medium reserve abundance with medium formation pressure potential zone, medium-high reserve abundance with medium formation pressure potential zone, and high reserve abundance with low formation pressure potential zone. The zones with the greatest potential are Zone 3 and Zone 4.

[0078] To verify the correctness of the benefit development potential evaluation model, the model from December 2018 was selected, and its accuracy was verified by adjusting the development effects of the wells. The current development potential area of ​​the XX gas reservoir is distributed in JP1. 4 JP2 1 JP2 2 JP2 5 and JP3 6 The gas-bearing reservoir with the largest reserves is Xinchang JP2. 2 Gas layer and JP3 6 Gas layer. Xinchang JP2 2 The gas reservoir development potential area is located in the northern part of the reservoir, mainly consisting of low-abundance, high-formation-pressure type remaining reserves, with a remaining reserve of 15.32 × 10⁻⁶. 8 m 3 JP3 6 The gas reservoir's development potential areas are mainly distributed in the central and southern parts. The remaining reserves in the central part are mainly high-abundance, low-formation-pressure type remaining reserves, while the remaining reserves in the southern part are medium-abundance, high-formation-pressure type remaining reserves. The total remaining reserves with development potential in the gas reservoir are 6.65 × 10⁻⁶. 8 m 3 .

[0079] Based on the potential evaluation model, for JP2 2 and JP3 6Seventeen adjustment wells were deployed in the gas reservoir. Based on actual production, the actual net profit was calculated using the dynamic method to predict recoverable reserves, as shown in Table 2. Of the 17 wells, only two wells deployed in potential zones 5 and 1 had negative net profits, achieving a well count accuracy rate of 88% and a net profit of 10.87 million yuan, thus achieving the goal of evaluating the gas reservoir's potential.

[0080] Table 2. Statistical Table of Economic Benefits of Actual Production Wells

[0081] No potential area 3 -4343 -1448 Potential Zone 1 2 -2518 -1259 Potential Zone 2 1 305 305 Potential Zone 3 8 10465 1308 Potential Zone 4 2 3160 1580 Potential Zone 5 1 -538 -538

[0082] Step three involves establishing development technology strategies for different reserve areas, including well type selection, horizontal well optimization, selection of reasonable well spacing, and reasonable production rate.

[0083] Well type selection is the first consideration in gas reservoir well network deployment. Under current technological conditions and a gas price of 1404 yuan / thousand cubic meters, using an internal rate of return (IRR) of 8% as the economic evaluation criterion, this study investigates the minimum reserve abundance required for profitable development of the XX gas reservoir using vertical and horizontal wells. The profit relationship between different well types under different reserve abundance conditions is shown in the diagram below, assuming the formation pressure remains at the original formation pressure. Figure 11 As shown. The results indicate that the higher the abundance of the XX gas reservoir, the higher the profit regardless of whether vertical or horizontal wells are deployed. When the abundance is greater than 0.45 × 10⁻⁶... 8 m 3 / km 2 When the profit of vertical and horizontal wells is greater than 0, the corresponding reserve abundance is the minimum reserve abundance required for profitable development of that well type. Furthermore, as reserve abundance increases, the profit increase for horizontal wells is greater than that for vertical wells. When the reserve abundance exceeds 0.6 × 10⁻⁶... 8 m 3 / km 2 At this time, horizontal wells are slightly more profitable than vertical wells; when the reserve abundance is greater than 1.2×10 8 m 3 / km 2 Horizontal wells are far more profitable than vertical wells, making horizontal wells a more worthwhile option.

[0084] As formation pressure decreases, the profitability of different well types varies under different reserve abundance conditions, such as... Figure 12As shown in the figure, as formation pressure decreases, the required reserve abundance for efficient development using either vertical or horizontal wells increases, exhibiting a power-law relationship. When the formation pressure is relatively low, exceeding 70% of the original formation pressure, the required reserve abundance for efficient development using horizontal wells is lower than that required for vertical wells; the lower the pressure, the lower the required reserve abundance for horizontal wells compared to vertical wells. When the formation pressure is high, exceeding 70% of the original formation pressure, the required reserve abundance for efficient development using both vertical and horizontal wells is comparable, with vertical wells requiring slightly less. Considering the certain degree of superposition in the XX gas reservoir, and the ability to utilize multiple vertical wells for combined production in the superposition zone, vertical wells are preferred when the formation pressure is more than 70% higher than the original formation pressure.

[0085] For horizontal well optimization, numerical simulations were used to calculate the recoverable reserves of gas wells in Class I, II, and III reservoir areas when the length of the horizontal section of the horizontal well is 500m-1800m and when the number of fracturing sections in the horizontal section is 6-16. The cash flow method was used to calculate the profit obtained for different horizontal section lengths and the number of fracturing sections, and horizontal well optimization was carried out based on actual data.

[0086] Regarding the selection of reasonable well spacing, for vertical wells, the unsteady dynamic analysis method for tight sandstone gas reservoirs is used to calculate the gas leakage radius of a single well. In the XX gas reservoir, the average gas leakage radius of gas wells in Class I reservoirs is 337m, with a reasonable well spacing of 670m; in Class II reservoirs, the average gas leakage radius is 301m, with a reasonable well spacing of 600m; and in Class III reservoirs, the average gas leakage radius is 247m, with a reasonable well spacing of 490m. For horizontal wells, a typical well area of ​​the Penglaizhen Formation gas reservoir in western Sichuan is selected. With designed well spacings of 500-1200m, the recoverable reserves of the well area are simulated and calculated. The profit obtained from the well area is obtained using the cash flow method, and the optimal well spacing is determined.

[0087] Regarding the selection of reasonable production rates, for gas reservoirs like the Penglaizhen Formation that rely on their own energy for depletion-based extraction, the reasonable production allocation for a single well must be within the maximum production capacity of the well, fully utilizing the natural energy of the reservoir to improve the recovery rate of each well. Based on the actual development situation of the gas reservoir, methods such as the unobstructed flow rate method, trial production method, economic limit production method, and analogy method are used to demonstrate the reasonable production rate of a single well in the Penglaizhen Formation gas reservoir. Specifically, the unobstructed flow rate method and economic limit production method are used to calculate the reasonable production rate for vertical wells; while the economic limit production method and numerical simulation method are used for horizontal wells.

[0088] According to the gas reservoir potential evaluation model, the XX gas reservoir is located in JP2. 1 JP2 5 and JP3 6 The gas reservoir has the potential for infiltration and adjustment. A total of 8 infiltration and adjustment wells were deployed. The specific countermeasures are shown in Table 3. For uncontrolled residual gas, infiltration and adjustment were used to improve the recovery rate, adding 201 million cubic meters of recoverable reserves.

[0089] Table 3. Recommendations and Countermeasures for Deploying Infill Adjustment Wells in XX Gas Reservoir

[0090]

[0091]

[0092] According to the potential assessment model, the XX gas reservoir is located in JP2. 2 Northern gas layer and JP3 6 The undeveloped area in the southern part of the gas reservoir has further potential for profitable development. Based on the optimal development strategy for new wells in the XX gas reservoir JP2... 2 Eleven wells were deployed in the gas-bearing reservoir, as shown in Tables 4 and 5; in Xinchang JP3... 6 Nine wells were deployed in the gas reservoir, as shown in Table 4. For residual gas with high water saturation, 34 gas wells were deployed to enhance recovery using horizontal wells or new technologies, including 16 vertical wells and 18 horizontal wells. Twenty wells are already in production, adding 758 million cubic meters of recoverable reserves and increasing the recovery rate by 3.47%.

[0093] Table 4. Recommendations and Countermeasures for Vertical Well Location Deployment in XX Gas Reservoir

[0094]

[0095] Table 6. Recommendations and Countermeasures for Horizontal Well Location Deployment in XX Gas Reservoir

[0096]

[0097] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for establishing a map for the efficient development of low-abundance, low-permeability tight sandstone gas reservoirs, characterized in that, Includes the following steps: S1. Select a typical well area and determine the main controlling factors affecting the recovery rate based on the range of static geological characteristics of the well area using multi-factor sensitivity analysis. When conducting multi-factor sensitivity analysis, the geological factors affecting the recovery rate include porosity, permeability, effective thickness, water saturation, and formation pressure. The influence of geological factors on the recovery rate is calculated by the simultaneous change of multiple parameters. The main controlling factors affecting the recovery rate are formation pressure and reserve abundance. S2. Using dynamic and static methods, establish the relationship between net profit and recoverable reserves for different well types under different economic policies. These different economic policies include different internal rates of return (IRR) and different gas prices. The static method establishes the following relationship between net profit and recoverable reserves under different economic policies: The relationship between net profit and recoverable reserves under different economic policies, established using the dynamic method, is as follows: In the formula Net profit, in yuan; To accumulate gas production, 10 8 m 3 ; For oil and gas prices, in yuan / 10 3 m 3 ; Resource tax, % For income tax, % Total production cost, in yuan / 10 3 m 3 ; For the economically recoverable reserves, 10 8 m 3 ; Total operating cost, in yuan / 10 3 m 3 ; S3. Using typical well areas, predict the recoverable reserves of gas wells under different controlling factors. Combine the relationship between net profit and recoverable reserves to obtain the relationship between different controlling factors and net profit, i.e., the gas reservoir benefit development chart. Based on the relationship between different controlling factors and net profit, obtain the minimum reserve abundance for benefit development under different formation pressures. The specific method is as follows: based on the relationship between different formation pressures, different reserve abundances and net profit, make the net profit 0 to obtain the relationship between different formation pressures and minimum reserve abundances.

2. The method for establishing a development map of low-abundance, low-permeability tight sandstone gas reservoirs according to claim 1, characterized in that, The criteria for selecting typical well areas are: the recoverable reserves of the gas well are recovered to a degree greater than 60%, and the gas well has entered the low-pressure and low-production stage. Low pressure means that the wellhead pressure of the gas well is less than 2MPa, and low production means that the daily gas production of the gas well is less than 1000 cubic meters / day.

3. A method for the later-stage development of low-abundance, low-permeability tight sandstone gas reservoirs, characterized in that, Includes the following steps: Step 1: Obtain dynamic monitoring data of the target gas reservoir, and establish a numerical model of the gas reservoir based on the detailed three-dimensional model of the gas reservoir and constrained by the dynamic monitoring data; Step 2: Based on the gas reservoir numerical model, obtain the numerical distribution of different controlling factors of the target gas reservoir. Combine the gas reservoir benefit development map establishment benefit development potential evaluation model of the method for establishing a benefit development map of low-abundance and low-permeability tight sandstone gas reservoir according to any one of claims 1-2, and obtain the benefit development potential of any gas layer of the target gas reservoir at any time from production to abandonment, which is divided into potential area and no potential area. Step 3: Establish development technology strategies for different reserve areas, and deploy well locations according to the potential areas identified in Step 2 to achieve the later-stage benefit development of low-abundance, low-permeability tight sandstone gas reservoirs.

4. The method for developing low-abundance, low-permeability tight sandstone gas reservoirs in the later stages according to claim 3, characterized in that, The steps for establishing a gas reservoir numerical model based on gas reservoir dynamic monitoring data include: predicting gas reservoir production data using the refined three-dimensional gas reservoir model, comparing the predicted gas reservoir production data with the gas reservoir dynamic monitoring data, calculating the fitting rate of gas reservoir parameters, and considering that the gas reservoir numerical model prediction results are consistent with the actual production data if the fitting rate of gas reservoir parameters is >90%; otherwise, re-establishing the refined three-dimensional gas reservoir model by modifying the permeability and conductivity selected when establishing the refined three-dimensional gas reservoir model.

5. The method for developing low-abundance, low-permeability tight sandstone gas reservoirs in the later stages according to claim 3, characterized in that, The potential area is subdivided into six zones: low reserve abundance with high formation pressure potential zone, low reserve abundance with medium to high formation pressure potential zone, medium-low reserve abundance with medium to high formation pressure potential zone, medium reserve abundance with medium formation pressure potential zone, medium-high reserve abundance with medium formation pressure potential zone, and high reserve abundance with low formation pressure potential zone.

6. The method for developing low-abundance, low-permeability tight sandstone gas reservoirs in the later stages according to claim 3, characterized in that, Establishing technical strategies for developing different reserve areas includes well type selection, horizontal well optimization, selection of reasonable well spacing, and reasonable production.

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