A method for optimizing production control of the same layer in a low-permeability tight gas reservoir

Abstract

The present invention provides a method for optimizing the production and control of the same layer in a low-permeability tight gas reservoir, belonging to the technical field of oil and gas field development. First, the present invention constructs a reservoir parameter matrix, conducts stress sensitivity and starting pressure gradient tests, solves the equation by means of Laplace transform and Fourier series iteration method, calculates the drainage radius of each well, and constructs a drainage field description function. The well spacing coefficient is calculated according to the drainage radius of adjacent wells and the actual well spacing, and the pressure reduction wells, pressure increase wells and normal development wells are divided. The bottom hole flowing pressure is adjusted at a gradient of 0.1 MPa, the gradient projection optimization function is applied to calculate the optimal adjustment scheme, the well spacing coefficient and well type are re-evaluated, and a pressure stable change index is constructed. Iterative adjustment is carried out until all wells are normal development wells, or the area requiring densification is identified. Finally, the recommended bottom hole flowing pressure of all wells after optimization and control is obtained, and the balanced utilization of the reservoir and the optimization of production capacity are realized.

Description

Technical Field

[0001] The present invention belongs to the technical field of oil and gas field development, and specifically relates to a method for optimizing and regulating the production of the same layer in a low-permeability tight gas reservoir. Background Art

[0002] Low-permeability tight gas reservoirs are characterized by low reservoir permeability, complex pore structures, and gas-water two-phase flow, and are an important type of resource for current natural gas development. Traditional tight gas reservoir development mainly adopts a development mode with a dense well spacing and a fracturing technology to increase the reservoir conductivity, and controls the production capacity of production wells by adjusting the bottom-hole flowing pressure. However, these methods are usually based on single-well analysis and do not fully consider the well interference and the complex relationship of multi-well collaborative production in the same layer.

[0003] With the deepening of the development degree, tight gas reservoirs face problems such as enhanced stress sensitivity effects caused by reduced reservoir pressure and increased complexity of gas-water two-phase flow. Most of the existing technologies ignore the influence of stress sensitivity and starting pressure gradient on multi-well production, resulting in overlapping or insufficient coverage of the drainage radius between adjacent wells, uneven reservoir utilization, low well pattern efficiency, and production capacity loss. Especially in the multi-well production environment of the same layer, the mutual influence between production wells is difficult to accurately quantify and optimize and regulate.

[0004] At present, there is a lack of a systematic and efficient method for optimizing and regulating the production of multi-wells in the same layer of low-permeability tight gas reservoirs in engineering practice, and it is impossible to achieve accurate evaluation of well interference and coordinated regulation of flowing pressure under the influence of stress sensitivity and starting pressure gradient, which seriously restricts the improvement of the development efficiency of low-permeability tight gas reservoirs. Summary of the Invention

[0005] In view of this, the present invention provides a method for optimizing and regulating the production of the same layer in a low-permeability tight gas reservoir, which can solve the problem that in the prior art, in the process of multi-well collaborative regulation and optimization in the same layer of a low-permeability tight gas reservoir, the influence of stress sensitivity and starting pressure gradient cannot be accurately considered.

[0006] The present invention is implemented as follows: The present invention provides a method for optimizing the production control of the same layer in a low-permeability tight gas reservoir, which includes: constructing a basic reservoir parameter matrix, including reservoir physical property parameters, fluid parameters, and well development dynamic data; collecting production well core and fluid samples, conducting stress sensitivity tests and starting pressure tests, obtaining stress sensitivity coefficients and starting pressure gradients, and forming a stress sensitivity variation matrix; establishing a multiphase seepage control equation considering the influence of stress sensitivity coefficients and starting pressure gradients, introducing a gas-water two-phase pseudo-pressure function, and calculating the drainage radius of the production well; applying Laplace transform to solve the multiphase seepage control equation, calculating the drainage radius of each well through Fourier series iteration method, and establishing a drainage field description function; calculating the well spacing coefficient according to the drainage radius and well spacing, classifying well types and adjusting the bottom-hole flowing pressure; applying the gradient projection optimization function to calculate the optimal pressure adjustment plan, and iteratively adjusting until all wells are normal development wells.

[0007] Among them, the reservoir physical property parameters include the original formation permeability, formation thickness, and reservoir temperature, which are obtained from on-site logging interpretation data.

[0008] Among them, the fluid parameters include the original formation pressure, gas-phase viscosity, water-phase viscosity, gas-phase relative permeability, and water-phase relative permeability, which are obtained from on-site logging interpretation data and gas-liquid sampling tests.

[0009] Among them, the well development dynamic data include the production well location coordinates, bottom-hole flowing pressure, gas-phase flow rate under standard conditions, and water-phase flow rate under standard conditions, which are obtained from on-site production data.

[0010] Among them, the stress sensitivity variation matrix refers to the data set obtained through core tests to obtain the change law of reservoir rock permeability under different pressure conditions, characterizing the stress sensitivity characteristics of the reservoir, and measuring the minimum pressure gradient values required for the gas phase and liquid phase to flow in different cores.

[0011] Among them, the multiphase seepage control equation is used to describe the seepage law of gas-water two-phase in a tight reservoir considering the influence of stress sensitivity coefficients and starting pressure gradients. The inputs include the original formation permeability, stress sensitivity coefficient, original formation pressure, gas-phase relative permeability, water-phase relative permeability, gas-phase starting pressure gradient, and liquid-phase starting pressure gradient, and the outputs are the formation pressure and fluid seepage velocity at any distance from the wellbore center.

[0012] Among them, the well spacing coefficient refers to the ratio of the sum of the drainage radii of two adjacent wells to the actual well spacing; when the well spacing coefficient is less than 0.8, it is classified as a pressure-reducing well, when the well spacing coefficient is greater than 1.2, it is classified as a pressure-increasing well, and when the well spacing coefficient is between 0.8 and 1.2, it is a normal development well.

[0013] Among them, the gradient projection optimization function is used to find the optimal pressure adjustment plan under the condition of meeting the production bottom-hole flowing pressure constraint. The inputs include the initial bottom-hole flowing pressure, drainage radius, well spacing coefficient, pressure stability matrix, and pressure stability change index, and the outputs are the optimal bottom-hole flowing pressure of each production well and the corresponding change rate of the drainage radius.

[0014] Among them, the pressure stability change index refers to the percentage change in the drainage radius of each well before and after each adjustment during the adjustment process of the bottom-hole flowing pressure, which is an index used to quantitatively evaluate the influence of pressure adjustment on the reservoir utilization degree.

[0015] Among them, the pressure stability matrix refers to the data set formed by adjusting the bottom-hole flowing pressure in a 0.1 MPa gradient after dividing the well types according to the well spacing coefficient, which reflects the distribution state of the bottom-hole flowing pressure of each well during the adjustment process.

[0016] The present invention realizes the accurate calculation of the drainage radius of production wells and the scientific evaluation of the well spacing coefficient by constructing a multiphase seepage mathematical model considering the influence of stress sensitivity and starting pressure gradient, and then reasonably divides the production well types based on the well spacing coefficient and implements targeted flowing pressure control.

[0017] This method overcomes the limitations of traditional technologies that ignore the influence of stress sensitivity and starting pressure gradient. By introducing the pseudo-pressure function of gas-water two-phase and applying Laplace transform to solve the seepage equation, a description function of the drainage field is established, and the degree of well interference is accurately quantified. Based on the iterative pressure regulation strategy of the gradient projection optimization function, the scientific adjustment of the bottom-hole flowing pressure is realized, and the problems of overlapping or insufficient coverage of the drainage radius of adjacent wells are avoided.

[0018] The present invention successfully solves the problem of multi-well collaborative regulation and optimization during the production process of the same layer in low-permeability tight gas reservoirs, realizes the improvement of the balance of reservoir utilization, the enhancement of well pattern development efficiency, and the optimization of overall productivity, and provides scientific technical support for the efficient development of low-permeability tight gas reservoirs. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 It is a flow chart of the method of the present invention.

[0020] Figure 2 It is a flow chart of the method for calculating the drainage radius between two adjacent wells based on the iterative method in Embodiment 2.

[0021] Figure 3 It is a schematic diagram of the relative positions of three tight gas wells in an embodiment of Embodiment 2.

[0022] Figure 4 It is a schematic diagram of the drainage radius of production wells before and after production optimization adjustment in an embodiment of Embodiment 2, where sub-figure (a) is a schematic diagram of the drainage radius of three wells before optimization, and sub-figure (b) is a schematic diagram of the drainage radius of three wells after optimization. Detailed implementation manners

[0023] To make the objectives, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.

[0024] As Figure 1 shown, it is a flowchart of a method for optimizing the production and control of the same layer in a low-permeability tight gas reservoir provided by the present invention. The method includes the following steps:

[0025] S01. Construct a basic reservoir parameter matrix, collect the reservoir physical property parameters, fluid parameters and well development dynamic data of the target gas reservoir, and establish a basic matrix;

[0026] S02. Collect core and fluid samples of production wells, conduct stress sensitivity tests and startup pressure tests, obtain the stress sensitivity coefficients of different cores, gas phase startup pressure gradients and liquid phase startup pressure gradients, and form a stress sensitivity change matrix;

[0027] S03. Establish a multiphase seepage control equation, consider the influence of stress sensitivity coefficients and startup pressure gradients, construct a differential equation of gas-water radial seepage motion, introduce the pseudo-pressure function of gas-water two-phase, and calculate the drainage radius of production wells;

[0028] S04. Apply Laplace transform to solve the multiphase seepage control equation, transform it into a second-order differential equation according to the boundary conditions, calculate the drainage radius of each well by Fourier series iteration method, and establish a drainage field description function;

[0029] S05. Calculate the well spacing coefficient according to the drainage radius of adjacent production wells and the actual well spacing, judge the adjustment type of production wells. When the well spacing coefficient is less than 0.8, it is classified as a pressure reduction well. When the well spacing coefficient is greater than 1.2, it is classified as a pressure increase well. When the well spacing coefficient is between 0.8 and 1.2, it is a normal development well;

[0030] S06. Adjust the bottom hole flowing pressure at a gradient of 0.1 MPa, reduce the bottom hole flowing pressure of the pressure reduction wells, increase the bottom hole flowing pressure of the pressure increase wells, and establish a pressure stability matrix;

[0031] S07. Apply the gradient projection optimization function to calculate the optimal pressure adjustment scheme, recalculate the drainage radius according to the adjusted bottom hole flowing pressure, update the well spacing coefficient and well type, and construct a pressure stability change index;

[0032] S08. Judge whether the bottom hole flowing pressure of the pressure reduction wells reaches the on-site minimum required value. If it reaches and it is still an adjustment well, then conduct a study on well pattern infill for the area;

[0033] S09. Judge whether all wells are normal development wells. If satisfied, obtain the recommended bottom hole flowing pressures of all wells after optimization and control. If not satisfied, return to step S06 for readjustment.

[0034] Among them, the basic matrix refers to a two-dimensional data set that characterizes the characteristics and production situation of a gas reservoir by collecting the basic parameters of the gas reservoir, including reservoir physical property parameters, fluid parameters, and well development dynamic data. The rows represent different well positions, and the columns represent different parameter types.

[0035] Among them, the stress-sensitive variation matrix refers to a data set that characterizes the stress-sensitive characteristics of the reservoir by obtaining the variation law of reservoir rock permeability under different pressure conditions through core tests, and measures the minimum pressure gradient values required for the gas phase and liquid phase to flow in different cores.

[0036] Among them, the pressure stability matrix refers to a data set formed by dividing well types according to the well spacing coefficient and adjusting the bottom-hole flowing pressure at a gradient of 0.1 MPa, reflecting the distribution state of the bottom-hole flowing pressure of each well during the adjustment process.

[0037] Among them, the pressure stability change index refers to an index used to quantitatively evaluate the impact of pressure adjustment on the reservoir utilization degree by calculating the percentage change in the drainage radius of each well before and after each adjustment during the adjustment process of the bottom-hole flowing pressure.

[0038] Among them, the well spacing coefficient refers to the ratio of the sum of the drainage radii of two adjacent wells to the actual well spacing, which is used to judge the degree of well interference and the reservoir utilization efficiency, and is a key index for screening production adjustment wells.

[0039] Among them, the reservoir physical property parameters include the original formation permeability, formation thickness, and reservoir temperature, which are obtained from on-site well logging interpretation data.

[0040] Among them, the fluid parameters include the original formation pressure, gas-phase viscosity, water-phase viscosity, gas-phase relative permeability, and water-phase relative permeability, which are obtained from on-site well logging interpretation data and gas-liquid sampling tests.

[0041] Among them, the well development dynamic data includes the production well location coordinates, bottom-hole flowing pressure, gas-phase flow rate under standard conditions, and water-phase flow rate under standard conditions, which are obtained from on-site production data.

[0042] The multiphase seepage control equation is used to describe the seepage law of gas-water two-phase in a tight reservoir considering the influence of stress-sensitive coefficient and starting pressure gradient. The inputs include the original formation permeability, stress-sensitive coefficient, original formation pressure, gas-phase relative permeability, water-phase relative permeability, gas-phase starting pressure gradient, and liquid-phase starting pressure gradient, and the outputs are the formation pressure and fluid seepage velocity at any distance from the wellbore center.

[0043] The gradient projection optimization function is used to find the optimal pressure adjustment scheme under the condition of satisfying the production bottom-hole flowing pressure constraint. The inputs include the initial bottom-hole flowing pressure, drainage radius, well spacing coefficient, pressure stability matrix, and pressure stability change index, and the outputs are the optimal bottom-hole flowing pressure of each production well and the corresponding change rate of the drainage radius.

[0044] The specific implementation manners of the above steps are described in detail below. The specific implementation manner of step S01 is to collect and sort out comprehensive data of the target gas reservoir to form a basic parameter matrix of the reservoir. First, collect the reservoir physical property parameters of the low-permeability tight gas reservoir, including parameters such as original formation permeability, formation thickness, reservoir temperature, etc., which are mainly obtained through well logging interpretation; then collect fluid parameters, including original formation pressure, gas phase viscosity, water phase viscosity, gas phase relative permeability, water phase relative permeability, which are obtained through on-site well logging interpretation data and gas-liquid sampling tests; finally, collect well development dynamic data, including production well location coordinates, bottom hole flowing pressure, gas phase flow rate under standard conditions, water phase flow rate under standard conditions, which are obtained through on-site production data collection. Matrixize the collected various data according to well positions and parameter types to construct a two-dimensional data set representing the characteristics and production conditions of the gas reservoir, that is, the basic matrix, providing a data basis for subsequent production optimization and control.

[0045] The specific implementation manner of step S02 is to conduct experimental tests on the cores and fluid samples of the production wells to obtain the stress sensitivity characteristics and starting pressure parameters of the low-permeability tight gas reservoir. First, conduct stress sensitivity tests on the collected core samples to measure the change in reservoir rock permeability under different pressure conditions and determine the stress sensitivity coefficient. Generally, the value range of the stress sensitivity coefficient is 0.02 - 0.08; then conduct starting pressure tests on the reservoir fluid to measure the gas phase starting pressure gradient and the liquid phase starting pressure gradient. The gas phase starting pressure gradient is generally 0.01 - 0.05 MPa / m, and the liquid phase starting pressure gradient is generally 0.05 - 0.15 MPa / m. The stress sensitivity coefficient, gas phase starting pressure gradient, and liquid phase starting pressure gradient obtained through experimental tests constitute a stress sensitivity change matrix, providing key parameters for calculating the drainage radius.

[0046] The specific implementation manner of step S03 is to construct a multiphase seepage control equation. Considering the characteristics of strong stress sensitivity in the tight gas reservoir and the need for fluid flow to overcome the critical pressure gradient, select a point around any vertical well in the target interval of the reservoir, and establish a gas-water radial seepage motion differential equation considering the influence of the starting pressure gradient and stress sensitivity. This equation describes the relationship between the gas phase seepage velocity and the water phase seepage velocity and the pressure gradient and the starting pressure gradient, where the dynamic change of permeability caused by stress sensitivity influence is considered. Then, use the relationship between the fluid seepage velocity and production in the formation, as well as the relationship between the gas flow rate under standard conditions and the formation conditions and the state equation that the formation volume factor of formation water is approximately that of liquid, to derive the gas-water two-phase seepage differential equation under standard conditions. Introduce the gas-water two-phase pseudo-pressure function, simplify the calculation process through integral transformation, and establish a parameter relationship formula at any radius from the wellbore center, laying a theoretical foundation for calculating the drainage radius.

[0047] The specific implementation of step S04 is to solve the multiphase seepage control equation by mathematical methods. First, the Laplace transform is applied to convert the time domain to the complex domain and transform the partial differential equation into an ordinary differential equation. Then, according to the boundary conditions, including the bottom-hole flowing pressure being constant at the wellbore radius for the inner boundary and the formation pressure being unchanged at the well control reserve boundary for the outer boundary, the problem is transformed into a second-order differential equation. Next, the Fourier series iteration method is used to solve the differential equation by gradually iterative calculation to determine the drainage radius of each production well. The specific iterative process is as follows: start the iteration from the bottom hole, use the wellbore radius as the initial value, gradually increase the pressure increment by 0.1 MPa, calculate the corresponding radius until the pressure gradient is less than the gas-phase starting pressure gradient, and then stop the iteration. The obtained radius is the drainage radius. A drainage field description function is constructed through the drainage radius to provide a basis for calculating the well spacing coefficient later.

[0048] The specific implementation of step S05 is to determine the adjustment type of each production well according to the calculated drainage radius. First, calculate the well spacing coefficient between two adjacent wells, which is equal to the sum of the drainage radii of the two wells divided by the actual well spacing. Then, classify the well types according to the well spacing coefficient. When the well spacing coefficient is less than 0.8, the two adjacent production wells are classified as pressure-reducing wells, indicating that the distance between the wells is relatively large and the reservoir resources are not fully utilized. When the well spacing coefficient is greater than 1.2, the two adjacent production wells are classified as pressure-increasing wells, indicating that the interference between the wells is strong and the production pressure needs to be adjusted. When the well spacing coefficient is between 0.8 and 1.2, the well is classified as a normally developed well and no adjustment is required. If a well is classified as both a pressure-reducing well and a pressure-increasing well at the same time, then this well is listed as a pressure-increasing well. The well spacing coefficient threshold can be adjusted according to the gas reservoir development stage, appropriately reducing the 0.8 threshold at the initial stage of development and appropriately increasing the 1.2 threshold in the middle stage of development.

[0049] The specific implementation of step S06 is to adjust the bottom-hole flowing pressure according to the well types classified in step S05. For pressure-reducing wells, gradually reduce the bottom-hole flowing pressure at a gradient of 0.1 MPa to increase the drainage radius and improve the degree of resource utilization. For pressure-increasing wells, gradually increase the bottom-hole flowing pressure at a gradient of 0.1 MPa to reduce the drainage radius and reduce the interference between the wells. Through adjustment, a data set of the bottom-hole flowing pressures of all wells, that is, the pressure stability matrix, is formed. This matrix reflects the distribution state of the bottom-hole flowing pressures of each well during the adjustment process and provides data support for evaluating the adjustment effect. The adjustment of the bottom-hole flowing pressure should consider the actual situation on site. Generally, the minimum value of the bottom-hole flowing pressure of pressure-reducing wells is not lower than 2 MPa, and the maximum value of the bottom-hole flowing pressure of pressure-increasing wells does not exceed 85% of the original formation pressure.

[0050] The specific implementation of step S07 is to calculate the optimal pressure adjustment plan by applying the gradient projection optimization function. The gradient projection optimization function is based on the nonlinear programming theory and searches for the optimal pressure adjustment plan under the condition of meeting the bottom-hole flowing pressure constraint. This function takes the initial bottom-hole flowing pressure, drainage radius, well spacing coefficient, pressure stability matrix, and pressure stability change index as inputs, and generates the optimal bottom-hole flowing pressure of each production well and the corresponding drainage radius change rate through iterative calculation. Then, the drainage radius of each well is recalculated according to the adjusted bottom-hole flowing pressure, and the well spacing coefficient and well type division are updated. At the same time, a pressure stability change index is constructed. This index quantifies and evaluates the impact of pressure adjustment on the reservoir utilization degree by calculating the percentage change in the drainage radius of each well before and after each adjustment, providing a quantitative index for judging the adjustment effect. The pressure stability change index generally requires not to be lower than 5%, indicating that the adjustment has a substantial effect.

[0051] The specific implementation of step S08 is to evaluate the state of the adjusted pressure reduction wells. For the pressure reduction wells adjusted through steps S06 and S07, it is judged whether their bottom-hole flowing pressure has reached the minimum value required on-site, generally 2 MPa. If the bottom-hole flowing pressure has dropped to the minimum value, but the well spacing coefficient is still less than 0.8, it means that effective control of reservoir resources cannot be achieved simply by adjusting the bottom-hole flowing pressure, and it is necessary to carry out research on well pattern infilling in this area to optimize the reservoir resource utilization degree through well pattern infilling. The well pattern infilling plan should comprehensively consider the remaining gas distribution law, reservoir heterogeneity, and economic factors to determine the location and number of infilling wells. The infilling well spacing generally takes 0.5 - 0.7 times of the original well pattern.

[0052] The specific implementation of step S09 is to evaluate the optimization and control results. By judging whether all wells are normal development wells, that is, whether the well spacing coefficients of all wells are between 0.8 and 1.2, it is determined whether the optimization goal is achieved. If the conditions are met, it indicates that the drainage radius distribution of each well is reasonable after optimization and control, the well interference degree is moderate, and the reservoir resource utilization efficiency is high, and the recommended bottom-hole flowing pressure of all wells can be obtained finally to achieve the long-term stable production of the gas reservoir; if the conditions are not met, return to step S06 to continue adjusting the bottom-hole flowing pressure until the optimization goal is achieved. The evaluation indexes of the optimization and control results include that the overall drainage radius coverage rate of the block is not less than 80%, the standard deviation of the well spacing coefficient does not exceed 0.2, and the average pressure stability change index is not less than 8%.

[0053] The following details the mathematical models or calculation processes involved in the present invention.

[0054] In step S01, to construct the reservoir basic parameter matrix, it is necessary to collect the reservoir physical property parameters, fluid parameters, and well development dynamic data of the target gas reservoir. The basic matrix is expressed as:

[0055] ;

[0056] In the formula, is the base matrix; is the th parameter value of the th well; is the total number of production wells in the gas reservoir; is the total number of parameters collected.

[0057] Among them, the parameter acquisition method is as follows: reservoir physical property parameters are obtained through on-site logging interpretation, fluid parameters are obtained through on-site logging interpretation data and gas-liquid sampling tests, and well development dynamic data are obtained through on-site production data collection. The parameters in the base matrix include original formation permeability, formation thickness, reservoir temperature, original formation pressure, gas-phase viscosity, water-phase viscosity, gas-phase relative permeability, water-phase relative permeability, production well location coordinates, bottom-hole flowing pressure, gas-phase flow rate under standard conditions, water-phase flow rate under standard conditions, etc.

[0058] In step S02, the stress-sensitive variation matrix is expressed as:

[0059] ;

[0060] In the formula, is the stress-sensitive variation matrix; is the stress-sensitive coefficient of the th well core, dimensionless; is the gas-phase starting pressure gradient of the th well core, MPa / m; is the liquid-phase starting pressure gradient of the th well core, MPa / m.

[0061] The acquisition method of the stress-sensitive coefficient is as follows: measure the permeability of the core sample under different effective stress conditions, and then obtain it through exponential fitting:

[0062] ;

[0063] In the formula, is the current permeability, ; is the original formation permeability, ; is the original formation pressure, MPa; is the current formation pressure, MPa. The experimental steps include: loading the core sample into a high-pressure core holder, adjusting the confining pressure to simulate the formation effective stress, using gas (usually nitrogen) as the seepage medium, measuring the core permeability under different confining pressure conditions, and obtaining the stress-sensitive coefficient through data fitting.

[0064] Gas startup pressure gradient and liquid startup pressure gradient can be obtained by: through unsteady-state seepage experiments, gradually increase the pressure gradient until fluid flow is observed to start, and record the pressure gradient at this time as the startup pressure gradient. The experimental steps include: saturate the core sample with the fluid to be measured, apply an initial pressure difference, gradually increase the pressure difference and record the flow rate. The pressure gradient corresponding to when the flow rate starts to change from zero is the startup pressure gradient.

[0065] In steps S03 and S04, the differential equation of gas-water radial seepage motion considering the startup pressure gradient and stress sensitivity effects is:

[0066] ;

[0067] ;

[0068] In the formula, is the gas-phase seepage velocity, m / s; is the water-phase seepage velocity, m / s; is the gas-phase relative permeability; is the water-phase relative permeability; is the gas-phase viscosity under formation conditions, Pa·s; is the water-phase viscosity under formation conditions, Pa·s; is the radius from the wellbore center, m; is the pressure gradient in the

[0069] The relationship between the seepage velocity of the fluid in the formation and the production is:

[0070] ;

[0071] In the formula, is the fluid seepage velocity, m / s; is the flow rate of the gas well produced fluid under reservoir conditions, ; is the thickness of the tight sandstone gas reservoir, m.

[0072] The relationship between the gas flow rate under standard conditions and formation conditions is:

[0073] ;

[0074] In the formula, is the gas-phase flow rate under reservoir conditions, ; is the gas-phase flow rate under standard conditions, ; is the standard atmospheric pressure, taken as 0.1 MPa; is the gas deviation factor, dimensionless; is the absolute reservoir temperature, K; is the gas deviation factor under standard conditions, taken as 1; is the temperature under standard conditions, taken as 293.15 K.

[0075] The formation water volume factor is approximately the liquid state equation:

[0076] ;

[0077] In the formula, is the water phase flow rate under reservoir conditions, ; is the formation water volume factor, dimensionless; is the water phase flow rate under standard conditions, .

[0078] After arrangement, the differential equation of gas-water two-phase seepage under standard conditions is obtained:

[0079] ;

[0080] The gas-water two-phase pseudo-pressure function is introduced:

[0081] ;

[0082] In the formula, is the pseudo-pressure function, MPa / MPa·s; is the bottom hole flowing pressure, MPa.

[0083] For any radius 、 () and the corresponding 、 、 at the wellbore center, the integral gives the formula:

[0084] ;

[0085] The representation form of the parameters is:

[0086] ;

[0087] ;

[0088] The drainage radius of a horizontal well is regarded as an ellipse, and the relationship between the short axis length of the elliptical seepage field and the radius of the equivalent circular seepage field is:

[0089] ;

[0090] In the formula, is the equivalent circular seepage field radius, m; is the minor axis length of the elliptical seepage field, m; is the horizontal section length of the horizontal well, m.

[0091] Based on the above equations, the iterative method is used to solve the drainage radius of the production well:

[0092] ;

[0093] In the formula, is the drainage radius, m; is the bottom-hole flowing pressure, MPa.

[0094] In step S05, the calculation formula for the well spacing coefficient is:

[0095] ;

[0096] In the formula, is the well spacing coefficient, dimensionless; , are the drainage radii of two adjacent production wells in the same layer, m; is the actual well spacing between two adjacent wells, m.

[0097] In step S06, the pressure stability matrix is expressed as:

[0098] ;

[0099] In the formula, is the pressure stability matrix; is the bottom-hole flowing pressure of the th well after the th adjustment, MPa; is the total number of adjustments.

[0100] In step S07, the gradient projection optimization function can be expressed as:

[0101] ;

[0102] ;

[0103] In the formula, is the optimization objective function; is the bottom-hole flowing pressure adjustment vector, MPa; is the weight coefficient, reflecting the importance degree of the th well; is the drainage radius of the th well before adjustment, m; is the drainage radius of the th well after adjustment, m; is the penalty coefficient, which controls the deviation degree of the well spacing coefficient; is the well spacing coefficient after adjustment for the th well; is the minimum bottom hole flowing pressure allowed for the th well, generally taken as 2 MPa; is the maximum bottom hole flowing pressure allowed for the th well, generally taken as 85% of the original formation pressure.

[0104] The calculation formula for the pressure stability change index is:

[0105] ;

[0106] In the formula, is the pressure stability change index of the th well, %.

[0107] The multiphase seepage control equation for implementing this scheme takes into account two key factors: stress sensitivity and starting pressure gradient, which are typical characteristics of low-permeability tight gas reservoirs. Stress sensitivity is expressed by the exponential function , reflecting the physical phenomenon that as the formation pressure decreases, the effective stress increases, resulting in a decrease in permeability. The starting pressure gradient is realized by introducing and terms into Darcy's law, describing the minimum pressure gradient threshold that the fluid needs to overcome in a tight medium, which conforms to the characteristics of non-Darcy seepage. The introduction of the pseudo-pressure function simplifies the solution process, transforming the complex nonlinear differential equation into a solvable form. The design of the well spacing coefficient takes into account the mutual influence between adjacent wells, providing a quantitative evaluation criterion for production optimization. The gradient projection optimization function comprehensively considers two objectives: the change of the drainage radius and the well spacing coefficient, realizing multi-objective optimization under constraints.

[0108] Specifically, the principle of the present invention is: The core principle of the method of the present invention is based on multiphase seepage mechanics and optimization control theory, constructing a mathematical model considering the influence of stress sensitivity and starting pressure gradient, and realizing the optimized regulation of multi-well production in the same layer of low-permeability tight gas reservoirs. This method first obtains the reservoir stress sensitivity coefficient and the gas-liquid two-phase starting pressure gradient through experimental measurement, and introduces these key parameters into the multiphase seepage control equation, enabling the mathematical model to accurately describe the special flow characteristics of tight gas reservoirs.

[0109] The Laplace transform is applied to solve the constructed differential equations of gas-water radial seepage motion, and through the Fourier series iteration method, the accurate calculation of the drainage radius of the production well is realized. As a key parameter characterizing the influence range of the wellbore, by introducing the pseudo-pressure function of gas-water two-phase, the calculation difficulties caused by non-linear seepage in the traditional method are overcome. Based on the calculated drainage radius, the method innovatively proposes the concept of well spacing coefficient as a scientific basis for judging the degree of well interference and well type division.

[0110] In the optimization and regulation stage, the present invention applies the gradient projection optimization function to finely adjust the bottom-hole flowing pressure with a gradient of 0.1 MPa, realizing the differential management of the pressure reduction wells and pressure increase wells. During the adjustment process, a pressure stable change index evaluation mechanism is introduced to ensure that each adjustment can move towards the overall optimization direction. Through iterative optimization, the method finally realizes the goal of converting all wells into normal development wells, or identifies the areas where well pattern densification is required, thus realizing the collaborative optimized production of multiple wells in the same layer of low-permeability tight gas reservoirs under the influence of stress sensitivity and starting pressure gradient.

[0111] A specific embodiment 1 of the present invention is provided below, and the specific implementation manners of each step in this embodiment 1 are described in detail as follows.

[0112] The specific implementation manner of step S01 is to form a basic reservoir parameter matrix through comprehensive data collection and arrangement of the target gas reservoir. First, collect the reservoir physical property parameters of the low-permeability tight gas reservoir, including original formation permeability, formation thickness, reservoir temperature and other parameters, which are mainly obtained through well logging interpretation; then collect the fluid parameters, including original formation pressure, gas phase viscosity, water phase viscosity, gas phase relative permeability, water phase relative permeability, which are obtained through on-site well logging interpretation data and gas-liquid sampling tests; finally, collect the well development dynamic data, including production well location coordinates, bottom-hole flowing pressure, gas phase flow rate under standard conditions, water phase flow rate under standard conditions, which are obtained through on-site production data collection. Matrixize the collected various data according to well positions and parameter types to construct a two-dimensional data set representing the gas reservoir characteristics and production conditions, that is, the basic matrix, and the basic matrix is expressed as: , where is the basic matrix; is the th parameter value of the th well; is the total number of production wells in the gas reservoir; is the total number of collected parameters. This matrix provides a data basis for subsequent production optimization and regulation, and through matrixization, it is beneficial to program the implementation of the optimization algorithm.

[0113] The specific implementation of step S02 is to conduct experimental tests on production well cores and fluid samples to obtain the stress sensitivity characteristics and startup pressure parameters of low-permeability tight gas reservoirs. First, stress sensitivity tests are conducted on the collected core samples to measure the changes in reservoir rock permeability under different pressure conditions and determine the stress sensitivity coefficient. Generally, the stress sensitivity coefficient ranges from 0.02 to 0.08. Then, startup pressure tests are conducted on the reservoir fluids to measure the gas-phase startup pressure gradient and the liquid-phase startup pressure gradient. The gas-phase startup pressure gradient is generally 0.01 to 0.05 MPa / m, and the liquid-phase startup pressure gradient is generally 0.05 to 0.15 MPa / m. The stress sensitivity coefficient, gas-phase startup pressure gradient, and liquid-phase startup pressure gradient obtained through experimental tests constitute the stress sensitivity variation matrix, which is expressed as: , where is the stress sensitivity variation matrix; is the stress sensitivity coefficient of the core of the th well, dimensionless; is the gas-phase startup pressure gradient of the core of the th well, MPa / m; is the liquid-phase startup pressure gradient of the core of the th well, MPa / m. The method for obtaining the stress sensitivity coefficient is as follows: Measure the permeability of the core sample under different effective stress conditions, and then obtain it through exponential fitting: , where is the current permeability; is the original formation permeability; is the original formation pressure; is the current formation pressure. This matrix provides key parameters for calculating the drainage radius.

[0114] The specific implementation of step S03 is to construct a multiphase seepage control equation. Considering the characteristics of strong stress sensitivity in tight gas reservoirs and the need for fluid flow to overcome the critical pressure gradient, a point is selected around any vertical well in the target reservoir section to establish a gas-water radial seepage motion differential equation considering the influence of the startup pressure gradient and stress sensitivity. This differential equation is: and , where is the gas-phase seepage velocity, m / s; is the water-phase seepage velocity, m / s; is the gas-phase relative permeability; is the water-phase relative permeability; is the gas-phase viscosity under formation conditions, Pa·s; is the water-phase viscosity under formation conditions, Pa·s; is the radius from the wellbore center, m; is The pressure gradient in the direction, MPa / m. Then, using the relationship between the fluid seepage velocity and the production rate in the formation: , where is the fluid seepage velocity, m / s; is the flow rate of the gas well produced fluid under reservoir conditions, ; is the thickness of the tight sandstone gas reservoir, m. And the relationship between the gas flow rates under standard conditions and reservoir conditions: , where is the gas-phase flow rate under reservoir conditions, ; is the gas-phase flow rate under standard conditions, ; is the atmospheric pressure under standard conditions, taking 0.1 MPa; is the gas deviation factor, dimensionless; is the absolute temperature of the reservoir, K; is the gas deviation factor under standard conditions, taking 1; is the temperature under standard conditions, taking 293.15 K. The volume coefficient of formation water is approximately the state equation of the liquid: , where is the water-phase flow rate under reservoir conditions, ; is the volume coefficient of formation water, dimensionless; is the water-phase flow rate under standard conditions, . After sorting, the differential equation of gas-water two-phase seepage under standard conditions is obtained: . Introduce the pseudo-pressure function of gas-water two-phase: , where is the pseudo-pressure function, MPa / MPa·s; is the bottom-hole flowing pressure, MPa. This equation describes the radial seepage law of gas-water two-phase considering the effects of stress sensitivity and starting pressure, laying a theoretical foundation for the calculation of the drainage radius.

[0115] The specific implementation of step S04 is to solve the multiphase seepage control equation by mathematical methods. First, apply the Laplace transform to convert the time domain to the complex domain and transform the partial differential equation into an ordinary differential equation; then, according to the boundary conditions, including the bottom-hole flowing pressure being constant at the wellbore radius for the inner boundary and the formation pressure being unchanged at the well control reserve boundary for the outer boundary, transform the problem into a second-order differential equation. For any radius , ( ) and the corresponding , , integrating gives the formula: , where the representation form of the parameters is: and For a horizontal well, the drainage radius is regarded as an ellipse. The relationship between the short axis length of the elliptical seepage field and the radius of the equivalent circular seepage field is as follows: , where is the radius of the equivalent circular seepage field, in m; is the short axis length of the elliptical seepage field, in m; is the length of the horizontal section of the horizontal well, in m. Then, the Fourier series iteration method is adopted to solve the differential equation by step-by-step iterative calculation to determine the drainage radius of each production well. The specific iterative process is as follows: Start the iteration from the bottom of the well, take the wellbore radius as the initial value, gradually increase the pressure increment by 0.1 MPa, calculate the corresponding radius, and stop the iteration until the pressure gradient is less than the gas-phase starting pressure gradient. The obtained radius is the drainage radius, , where is the drainage radius, in m. A drainage field description function is constructed through the drainage radius to provide a basis for the subsequent calculation of the well spacing coefficient.

[0116] The specific implementation of step S05 is to determine the adjustment type of each production well according to the calculated drainage radius. First, calculate the well spacing coefficient of two adjacent wells. The calculation formula for the well spacing coefficient is: , where is the well spacing coefficient, dimensionless; , are the drainage radii of two adjacent production wells in the same layer, in m; is the actual well spacing between two adjacent wells, in m. Then, classify the well types according to the well spacing coefficient. When the well spacing coefficient is less than 0.8, classify the two adjacent production wells as pressure-reducing wells, which means that the distance between the wells is relatively large and the reservoir resources are not fully utilized; when the well spacing coefficient is greater than 1.2, classify the two adjacent production wells as pressure-increasing wells, indicating that the interference between the wells is strong and the production pressure needs to be adjusted; when the well spacing coefficient is between 0.8 and 1.2, classify the well as a normally developed well and no adjustment is required. If a well is classified as both a pressure-reducing well and a pressure-increasing well at the same time, list this well as a pressure-increasing well. The well spacing coefficient threshold can be adjusted according to the gas reservoir development stage. Appropriately reduce the 0.8 threshold in the initial development stage and appropriately increase the 1.2 threshold in the middle development stage. Through the calculation and analysis of the well spacing coefficient, the scientific screening of production adjustment wells is realized.

[0117] The specific implementation of step S06 is to adjust the bottom hole flowing pressure according to the well types classified in step S05. For pressure-reducing wells, gradually reduce the bottom hole flowing pressure at a gradient of 0.1 MPa to increase the drainage radius and improve the resource utilization degree; for pressure-increasing wells, gradually increase the bottom hole flowing pressure at a gradient of 0.1 MPa to reduce the drainage radius and reduce the interference between the wells. Through adjustment, a bottom hole flowing pressure data set of all wells is formed, that is, a pressure stability matrix, and the pressure stability matrix is expressed as: , where is the pressure stability matrix; is the bottom-hole flowing pressure of the th well after the th adjustment, MPa; is the total number of adjustments. This matrix reflects the distribution state of the bottom-hole flowing pressure of each well during the adjustment process and provides data support for evaluating the adjustment effect. The adjustment of the bottom-hole flowing pressure should consider the actual situation on site. Generally, the minimum value of the bottom-hole flowing pressure of a pressure reduction well is not lower than 2 MPa, and the maximum value of the bottom-hole flowing pressure of a pressure increase well does not exceed 85% of the original formation pressure. By adjusting the bottom-hole flowing pressure in an orderly manner, the optimization of the resource control degree is realized.

[0118] The specific implementation of step S07 is to calculate the optimal pressure adjustment plan using the gradient projection optimization function. The gradient projection optimization function is based on the theory of nonlinear programming and finds the optimal pressure adjustment plan under the constraints of the bottom-hole flowing pressure. This function can be expressed as: , , where is the optimization objective function; is the bottom-hole flowing pressure adjustment vector, MPa; is the weight coefficient, reflecting the importance degree of the th well; is the drainage radius of the th well before adjustment, m; is the drainage radius of the th well after adjustment, m; is the penalty coefficient, controlling the deviation degree of the well spacing coefficient; is the well spacing coefficient of the th well after adjustment; is the minimum allowable bottom-hole flowing pressure of the th well, generally taking 2 MPa; is the maximum allowable bottom-hole flowing pressure of the th well, generally taking 85% of the original formation pressure. Then, recalculate the drainage radius of each well according to the adjusted bottom-hole flowing pressure, and update the well spacing coefficient and well type division. At the same time, construct the pressure stability change index. The calculation formula of the pressure stability change index is: , where is the pressure stability change index of the th well, %. This index quantifies the impact of pressure adjustment on the reservoir utilization degree by calculating the percentage change of the drainage radius of each well before and after each adjustment, and provides a quantitative index for judging the adjustment effect. Generally, the pressure stability change index is required to be not lower than 5%, indicating that the adjustment has a substantial effect. By optimizing the bottom-hole flowing pressure adjustment through the gradient projection method, the comprehensive optimization of the drainage radius and well spacing coefficient is realized.

[0119] The specific implementation of step S08 is to evaluate the adjusted state of the pressure-relief wells. For the pressure-relief wells adjusted through steps S06 and S07, it is judged whether the bottom-hole flowing pressure has reached the minimum value required on-site, generally 2 MPa. If the bottom-hole flowing pressure has dropped to the minimum value, but the well spacing coefficient is still less than 0.8, it indicates that effective control of reservoir resources cannot be achieved simply by adjusting the bottom-hole flowing pressure. It is necessary to carry out research on well pattern densification in this area to optimize the degree of reservoir resource utilization through well pattern densification. The well pattern densification plan should comprehensively consider the remaining gas distribution law, reservoir heterogeneity and economic factors to determine the location and number of infill wells. The infill well spacing is generally taken as 0.5 - 0.7 times of the original well pattern. Through the evaluation of well pattern densification, further measures for production adjustment are provided, ensuring the effective control of the overall reservoir resources.

[0120] The specific implementation of step S09 is to evaluate the optimization and control results. By judging whether all wells are normal development wells, that is, whether the well spacing coefficients of all wells are between 0.8 and 1.2, it is determined whether the optimization goal is achieved. If the conditions are met, it indicates that the drainage radius distribution of each well is reasonable after optimization and control, the degree of well interference is moderate, and the reservoir resource utilization efficiency is high. The recommended bottom-hole flowing pressure of all wells can be obtained finally to achieve the long-term stable production of the gas reservoir. If the conditions are not met, return to step S06 to continue adjusting the bottom-hole flowing pressure until the optimization goal is achieved. The evaluation indexes of the optimization and control results include that the overall drainage radius coverage rate of the block is not less than 80%, the standard deviation of the well spacing coefficient does not exceed 0.2, and the average pressure stable change index is not less than 8%. Through cyclic iterative optimization, it is ensured that the well spacing coefficients of all wells meet the requirements, realizing the optimal development effect of the whole gas reservoir.

[0121] To sum up, this embodiment fully considers the stress-sensitive characteristics and starting pressure gradient characteristics of low-permeability tight gas reservoirs, and constructs a drainage radius calculation model that better conforms to the actual reservoir characteristics. The degree of well interference is evaluated through the well spacing coefficient, production adjustment wells are scientifically selected, and the gradient projection optimization function is used to realize the optimal adjustment of the bottom-hole flowing pressure, improving the degree of resource control in the early and middle stages of the development of low-permeability tight gas reservoirs. This method not only establishes a complete theoretical model, but also provides practical engineering implementation steps, providing strong technical support for the efficient development of low-permeability tight gas reservoirs and having broad application prospects. Compared with the existing technology, this method more accurately characterizes the actual characteristics of the reservoir, has higher calculation efficiency, can quickly and effectively carry out production optimization and control, and lays a foundation for the long-term stable production of the gas reservoir.

[0122] To better understand and implement the present invention, the following provides Embodiment 2 of a specific application scenario of the present invention: In this embodiment, three adjacent tight gas wells producing from the same layer in a certain block in the middle of the Sulige Gas Field are selected, namely Well 1, Well 2 and Well 3. All three wells are vertical wells, and the production horizons are all Shan 1 of the Shanxi Formation. The relative position distribution of the three wells is shown inFigure 3 。

[0123] Step S01: Construct the basic reservoir parameter matrix. By collecting the logging data, fluid parameters and well development dynamic data of three wells, a basic matrix is established, as shown in Table 1:

[0124] Table 1 Basic parameters of three wells

[0125]

[0126] Step S02: Collect core and fluid samples from production wells and conduct stress sensitivity tests and startup pressure tests. Take multiple cores from each of the three wells for testing, and finally take the average of the test results of the same well as the final result to form a stress sensitivity variation matrix, as shown in Table 2:

[0127] Table 2 Stress sensitivity and startup pressure parameters of three wells

[0128]

[0129] Step S03: Establish the multiphase seepage control equation. Considering the characteristics of strong stress sensitivity in tight gas reservoirs and the need for fluid flow to overcome the critical pressure gradient, a differential equation for gas-water radial seepage motion is constructed. Introduce the gas-water two-phase pseudo-pressure function: , which is used to transform the complex gas-water two-phase seepage equation.

[0130] Step S04: Apply Laplace transform to solve the multiphase seepage control equation. According to the iterative method for calculating the drainage radius shown in Figure 2 , the specific process is as follows:

[0131] Perform initial assignment and start iteration from the bottom of the well: Set the iteration times of Well 1, Well 2 and Well 3 , and The initial assignment of Well 1 is set to , then , ; The initial assignment of Well 2 is set to , then , ; The initial assignment of Well 3 is set to , then , .

[0132] Substitute into the formula to calculate the pressure gradient at each step: Substitute the parameters into the formula to calculate , ; Substitute the parameters into the formula to calculate , ; Substitute the parameters into the formula to calculate , 。

[0133] Judge the termination condition according to the calculation result: not satisfied , the number of iterations 、 and assignment , , assignment , , assignment , , Return to step (2) and continuously repeat the iterative calculation.

[0134] Finally, the iteration ends, and the drainage radius is obtained: When , , the termination condition is satisfied and the iteration ends; When , , the termination condition is satisfied and the iteration ends; When , , the termination condition is satisfied and the iteration ends.

[0135] Step S05: Calculate the well spacing coefficient according to the drainage radius of adjacent production wells and the actual well spacing, and judge the type of production well adjustment. The well spacing of three wells: 、 、 , calculate the well spacing coefficient. According to the field requirements, the well spacing coefficient range of normal production wells is 0.95 - 1.20.

[0136] The well spacing coefficient between Well 1 and Well 2 , the two wells are classified as normal development wells, and the bottom hole flowing pressures of the two wells are not adjusted; the well spacing coefficient between Well 1 and Well 3 , the two wells are classified as pressurized wells; the well spacing coefficient between Well 2 and Well 3 , the two wells are classified as normal development wells, and the bottom hole flowing pressures of the two wells are not adjusted.

[0137] Step S06: Adjust the bottom hole flowing pressure at a gradient of 0.1 MPa. Carry out production optimization control for Well 1 and Well 3, raise the bottom hole flowing pressure of Well 1 to 8.0 MPa, raise the bottom hole flowing pressure of Well 3 to 8.0 MPa, and establish a pressure stability matrix as shown in Table 3:

[0138] Table 3 Pressure stability matrix

[0139]

[0140] Step S07: Calculate the optimal pressure adjustment plan using the gradient projection optimization function. Recalculate the drainage radius based on the adjusted bottom-hole flowing pressure, update the well spacing coefficient and well type, and construct the pressure stability change index.

[0141] Drainage radius after the first adjustment: , , Well spacing coefficient: , , Wells 1 and 3 are still boost wells and need to be further adjusted.

[0142] Drainage radius after the second adjustment: , , Well spacing coefficient: , , Wells 1 and 3 are still boost wells and need to be further adjusted.

[0143] Drainage radius after the third adjustment: , , Well spacing coefficient: , , All wells are normal production wells, meeting the optimization goal.

[0144] Step S08: Determine whether the bottom-hole flowing pressure of the pressure reduction well reaches the on-site minimum required value. In this embodiment, there is no situation where the bottom-hole flowing pressure of the pressure reduction well reaches the minimum required value but it is still an adjustment well, so there is no need to conduct research on well pattern densification.

[0145] Step S09: Determine whether all wells are normal development wells. After three adjustments, finally the well spacing coefficients between all wells fall within the range of 0.95 - 1.20, and all wells are normal development wells, meeting the optimization conditions. The optimized bottom-hole flowing pressure parameters are shown in Table 4 as follows:

[0146] Table 4 Comparison of bottom-hole flowing pressure and drainage radius before and after optimization

[0147]

[0148] Figure 4 (b) shows the schematic diagram of the optimized drainage radius of the three wells. It can be seen that through reasonable adjustment of the bottom-hole flowing pressure, the drainage radius of each well is optimized, and the resource control efficiency is significantly improved. The finally optimized bottom-hole flowing pressure is: MPa, MPa, MPa.

[0149] The traditional optimization of low-permeability tight gas reservoir production mainly relies on static analysis and engineering experience, without considering the effects of stress sensitivity and starting pressure gradient on reservoir flow, making it difficult to accurately calculate the drainage radius and determine a reasonable bottom-hole flowing pressure. The present invention establishes a multiphase seepage control equation considering stress sensitivity and starting pressure gradient, combines the Fourier series iteration method to calculate the drainage radius, uses the well spacing coefficient as the core index to judge the well type and conduct pressure regulation optimization, and realizes the refined control of the same-layer production in the gas reservoir. In the embodiment, the interference between the first three wells before optimization is uneven, the interference between Well 1 and Well 3 is too strong, and the well spacing coefficient reaches 1.288; after optimization by the method of the present invention, the well spacing coefficient between Well 1 and Well 3 is reduced to 1.194, while maintaining the well spacing coefficients between Well 1 and Well 2, and Well 2 and Well 3 at 0.951 and 0.972 respectively, all within a reasonable range, realizing the overall coordinated development of the gas reservoir, reducing the interference degree of multiple wells in the same layer by 34.52%, and increasing the recoverable reserves by about 5.37%.

[0150] It should be noted that the detailed explanations of the variables involved in the present invention are shown in Table 5 below.

[0151] Table 5 Variable Explanation Table

[0152]

[0153] As described above, the above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention can easily think of changes or substitutions, which should all be covered within the protection scope of the present invention.

Claims

1. A method for optimizing the production and control of the same layer in a low-permeability tight gas reservoir, characterized in that Including: S01. Construct a basic reservoir parameter matrix, collect reservoir physical property parameters, fluid parameters and well development dynamic data of the target gas reservoir, and establish a basic matrix; S02. Collect core and fluid samples of production wells, conduct stress sensitivity tests and startup pressure tests, obtain stress sensitivity coefficients of different cores, gas-phase startup pressure gradients and liquid-phase startup pressure gradients, and form a stress sensitivity change matrix; S03. Establish a multiphase seepage control equation, consider the influence of stress sensitivity coefficients and startup pressure gradients, construct a differential equation of gas-water radial seepage motion, introduce a pseudo-pressure function of gas-water two-phase, and calculate the drainage radius of production wells; S04. Apply Laplace transform to solve the multiphase seepage control equation, transform it into a second-order differential equation according to boundary conditions, calculate the drainage radius of each well by Fourier series iteration method, and establish a drainage field description function; S05. Calculate the well spacing coefficient according to the drainage radius of adjacent production wells and the actual well spacing, judge the type of production well adjustment. When the well spacing coefficient is less than 0.8, it is classified as a pressure reduction well. When the well spacing coefficient is greater than 1.2, it is classified as a pressure increase well. When the well spacing coefficient is between 0.8 and 1.2, it is a normally developed well; S06. Adjust the bottom-hole flowing pressure at a gradient of 0.1 MPa, reduce the bottom-hole flowing pressure of pressure reduction wells, increase the bottom-hole flowing pressure of pressure increase wells, and establish a pressure stability matrix; S07. Apply the gradient projection optimization function to calculate the optimal pressure adjustment plan, recalculate the drainage radius according to the adjusted bottom-hole flowing pressure, update the well spacing coefficient and well type, and construct a pressure stability change index; S08. Judge whether the bottom-hole flowing pressure of the pressure reduction well reaches the minimum required value on site. If it reaches and it is still an adjustment well, then conduct research on well pattern densification for the target gas reservoir; S09. Judge whether all wells are normally developed wells. If satisfied, obtain the recommended bottom-hole flowing pressures of all wells after optimized control. If not satisfied, return to step S06 for re-adjustment.

2. The method for optimizing and regulating the production of the same layer in a low-permeability tight gas reservoir according to claim 1, wherein Reservoir physical property parameters include original formation permeability, formation thickness, and reservoir temperature, which are obtained from on-site well logging interpretation data.

3. The method for optimizing and regulating the production of the same layer in a low-permeability tight gas reservoir according to claim 2, wherein Fluid parameters include original formation pressure, gas-phase viscosity, water-phase viscosity, gas-phase relative permeability, and water-phase relative permeability, which are obtained from on-site well logging interpretation data and gas-liquid sampling tests.

4. The method for optimizing the production and control of the same layer in a low-permeability tight gas reservoir according to claim 3, wherein Well development dynamic data include production well location coordinates, bottom-hole flowing pressure, gas-phase flow rate under standard conditions, and water-phase flow rate under standard conditions, which are obtained from on-site production data.

5. The method for optimizing and regulating the same-layer production of a low-permeability tight gas reservoir according to claim 4, wherein The multiphase seepage control equation is used to describe the seepage law of gas-water two-phase in tight reservoirs considering the influence of stress sensitivity coefficients and startup pressure gradients. The inputs include original formation permeability, stress sensitivity coefficients, original formation pressure, gas-phase relative permeability, water-phase relative permeability, gas-phase startup pressure gradient, and liquid-phase startup pressure gradient. The outputs are the formation pressure and fluid seepage velocity at any distance from the wellbore center.

6. The method for optimizing and regulating the production of the same layer in a low-permeability tight gas reservoir according to claim 5, wherein The gradient projection optimization function is used to find the optimal pressure adjustment plan under the constraint of production well bottom-hole flowing pressure. The inputs include initial bottom-hole flowing pressure, drainage radius, well spacing coefficient, pressure stability matrix, and pressure stability change index. The outputs are the optimal bottom-hole flowing pressures of each production well and the corresponding drainage radius change rate.

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