Method and system for measuring comprehensive compressibility coefficient of formation water

Abstract

The invention belongs to the technical field of oil and gas development, and discloses a formation water comprehensive compression coefficient measuring method and system.The method comprises the steps that a fracture network distribution rule and pore structure parameters are extracted; preparing a micro-fluidic chip; preparing formation water fluid containing dissolved gas, and injecting the formation water fluid into the micro-fluidic chip; carrying out a formation water failure development experiment under a reservoir in-situ condition, and recording gas-water saturation and pressure change in the micro-fluidic chip; quantifying the variation of the volume of the precipitated bubbles along with the pressure drop, and calculating a first compression coefficient contributed by the dissolved gas part and a second compression coefficient contributed by the formation water body part; and superposing the two coefficients to obtain the formation water comprehensive isothermal compression coefficient. According to the method, the formation water gassing expansion process can be monitored in real time, the formation water comprehensive isothermal compressibility coefficient can be more accurately calculated in combination with gas-water saturation and pressure change, and the problem that fluid seepage and fluid characteristics of the fractured low-porosity sandstone gas reservoir cannot be fully reflected is solved. The system has the same advantages as the method.

Description

Technical Field

[0001] This invention belongs to the field of oil and gas development technology, and in particular relates to a method and system for measuring the comprehensive compressibility coefficient of formation water. Background Technology

[0002] Fractured low-porosity sandstone gas reservoirs are a typical type of complex reservoir, characterized by high temperature and pressure, low porosity and permeability, but well-developed fractures, with natural gas primarily stored within these fractures. Development of such reservoirs typically employs a depletion-based extraction method, reducing formation pressure to allow natural gas to escape from the fractures. However, current technologies struggle to accurately simulate the microscopic depletion development process of fractured low-porosity sandstone gas reservoirs, particularly the formation water expansion process and its impact on reservoir development. Formation water plays a crucial role in fractured low-porosity sandstone gas reservoirs; its comprehensive isothermal compressibility coefficient is a vital parameter describing the volumetric change capacity of formation water under pressure variations, significantly impacting reservoir development effectiveness and reservoir evaluation.

[0003] In the development of fractured low-porosity sandstone gas reservoirs, the overall isothermal compressibility coefficient of formation water directly affects the flow characteristics of reservoir fluids and the elastic drive effect of the gas reservoir. Therefore, accurate measurement of the overall isothermal compressibility coefficient of formation water plays a crucial role in optimizing gas reservoir development schemes and improving recovery rates. However, due to the complexity of fractured low-porosity sandstone gas reservoirs, traditional measurement methods are difficult to accurately reflect the elastic compressibility characteristics of formation water at the microscale.

[0004] Specifically, the methods for measuring the composite isothermal compressibility coefficient of formation water can be mainly divided into the following categories: The first is the gas pressure test method, which is a commonly used method for measuring the composite isothermal compressibility coefficient of formation water. By simulating the compression process of formation water at a certain temperature, the relationship between the volume change and pressure change of water is directly measured. The second method is the core test method, which uses core samples taken from the formation to simulate water flow and pressure changes in the actual reservoir environment. This method can reflect the behavior of formation water in rock pores more realistically. The third method is theoretical calculation / numerical simulation. All of the above measurement methods have certain limitations. Although the gas pressure test method can simulate certain formation conditions, the environment of formation gas reservoirs is usually very complex, involving a variety of physical phenomena (such as stress, heterogeneity, pore structure, etc.). It is difficult to perfectly reproduce these complex environments in the laboratory, which leads to a certain deviation between the experimental results and the actual reservoir behavior. Gas pressure tests are usually conducted on core samples, which are extracted from large-scale reservoirs and may not fully represent the characteristics of the entire reservoir, especially when the reservoir has significant heterogeneity. The core test method can usually only test a limited number of samples extracted from the actual formation and cannot cover the various complex conditions of the entire oil and gas field or gas reservoir. Due to the locality of core samples, experimental results cannot fully represent the characteristics of the entire reservoir. Furthermore, core experiments are time-consuming, lack visualization, and cannot measure the comprehensive isothermal compressibility coefficient contributed by the gas component. In theoretical calculation / numerical simulation methods, theoretical calculation can serve as a supplementary means to assist in measuring the comprehensive isothermal compressibility coefficient of formation water. It is suitable for situations where there are no experimental conditions or time constraints. However, its results often have certain uncertainties and usually need to be combined with other methods (such as experiments, field data, etc.) for verification and calibration.

[0005] In general, traditional methods struggle to accurately reflect the elastic compressibility of formation water at the microscopic scale, especially in complex reservoirs. They cannot measure the compressibility coefficient contributed by dissolved gas in the formation water, and they cannot simultaneously satisfy the temperature, pressure, and fluid flow conditions of a real reservoir, leading to discrepancies between measurement results and actual formation conditions. Furthermore, traditional methods are typically based on macroscopic rock samples or ideal models, rather than a precise description of the microscopic pore structure of real rocks. This is particularly true in fractured, low-porosity sandstone gas reservoirs, where the pore system exhibits strong heterogeneity, low porosity and permeability, highly developed fractures, and tight coupling between fractures and the matrix. This structure is often simplified to regular geometry or average parameters in traditional experimental methods, neglecting the actual... The spatial connectivity, shape, and scale distribution of pores in reservoirs are crucial. Pore scales in reservoirs are often in the micrometer to nanometer range. Traditional experimental equipment struggles to fabricate precise, controllable, and scale-matched experimental models, making it impossible to replicate the complex microstructure of real reservoirs, especially the micropore structure. This results in insufficient simulation accuracy. Furthermore, long core displacement devices cannot observe the dynamic process of gas-water flow in real time, making it difficult to simulate fluid exchange between fractures and the matrix. They also cannot effectively reflect the impact of reservoir heterogeneity on fluid flow. They can only focus on the compressibility of liquid water without considering dissolved gas in formation water. Insufficient formation energy replenishment after depletion-type development leads to low subsequent recovery rates. Existing technologies are unable to effectively simulate fluid flow phenomena after formation energy replenishment. Summary of the Invention

[0006] To address the aforementioned issues, this invention provides a method and system for measuring the comprehensive compressibility coefficient of formation water. This method can more accurately simulate the microscopic pore structure, fracture network, and fluid flow behavior of fractured low-porosity sandstone gas reservoirs, realistically reflecting the depletion and development process of such reservoirs at the microscopic scale. Furthermore, it can effectively simulate the impact of reservoir heterogeneity on fluid flow and provide a theoretical basis for subsequent formation energy replenishment by simulating the depletion and development process, thereby improving gas recovery. Additionally, it can dynamically monitor the formation water gas expansion process in real time and, combined with changes in gas-water saturation and pressure, more accurately calculate the comprehensive isothermal compressibility coefficient of formation water, improving gas reservoir development efficiency and facilitating the development and evaluation of complex reservoirs.

[0007] The present invention provides a method for measuring the overall compressibility coefficient of formation water, comprising:

[0008] Based on the characteristics of the target gas reservoir, the distribution pattern of fracture network and pore structure parameters are extracted.

[0009] A microfluidic chip with the aforementioned crack network distribution pattern and pore structure parameters was prepared.

[0010] The composition of formation water in the target gas reservoir is obtained, a formation water fluid containing dissolved gas is prepared, and the formation water fluid containing dissolved gas is injected into the microfluidic chip.

[0011] Based on the microfluidic chip, a formation water depletion development experiment was conducted under in-situ reservoir conditions, and the gas-water saturation and pressure changes within the microfluidic chip were recorded.

[0012] The change in the volume of precipitated bubbles with pressure drop was quantified using image analysis software, and the first compressibility coefficient contributed by the dissolved gas was calculated.

[0013] Based on experimental conditions, the compressibility coefficient of the formation water volume was theoretically calculated, and the second compressibility coefficient contributed by the formation water volume was obtained.

[0014] The first compressibility coefficient and the second compressibility coefficient are superimposed to obtain the comprehensive isothermal compressibility coefficient of formation water.

[0015] Preferably, in the above-mentioned method for measuring the overall compressibility coefficient of formation water, the step of extracting the fracture network distribution pattern and pore structure parameters based on the characteristics of the target gas reservoir includes:

[0016] Porosity tests were performed on dry core samples from the target gas reservoir to obtain the reservoir's porosity parameters.

[0017] High-pressure mercury intrusion testing was performed on the dried core. Mercury was injected into the pores of the dried core under high pressure, and the size distribution of the pores was measured to obtain detailed pore throat structure information, providing pore radius parameters for the design of the microfluidic chip.

[0018] Structural scanning was performed on the dry core of the target gas reservoir to obtain a pore structure map of the interior of the dry core;

[0019] The pore structure image is binarized to obtain a pore distribution image. The pore structure features are statistically analyzed, and representative pore morphologies are selected.

[0020] Preferably, in the above-mentioned method for measuring the overall compressibility coefficient of formation water, the preparation of a microfluidic chip having the fracture network distribution pattern and the pore structure parameters includes:

[0021] Based on the porosity parameter, the pore radius parameter, and the representative pore morphology, random reconstruction is performed in the porous medium region of the microfluidic chip structure;

[0022] Based on random reconstruction, throats are generated using the Thiessen polygon algorithm or self-organizing map neural network algorithm to connect the pores. The coordination number and number of throats for each pore are set, and the resulting microfluidic chip structure is imported into CAD software.

[0023] Based on the microfluidic chip structure, the microfluidic chip is prepared by sequentially performing the following steps: coating, photolithography, development, etching, resist removal, etching, bonding, and wetting.

[0024] Preferably, in the above-mentioned method for measuring the overall compressibility coefficient of formation water, the step of obtaining the composition of the formation water in the target gas reservoir, preparing a formation water fluid containing dissolved gas, and injecting the formation water fluid containing dissolved gas into the microfluidic chip includes:

[0025] Analyze the gas composition of the target gas reservoir and prepare an equal proportion of gas as experimental gas;

[0026] The formation water composition and related mineralization standards of the target gas reservoir were analyzed, and brine with the corresponding mineralization was prepared as the experimental liquid.

[0027] The experimental gas and the experimental liquid are mixed in an intermediate container, and the pressure is increased to dissolve all the experimental gas into the experimental liquid, forming the formation water fluid containing dissolved gas.

[0028] The experimental apparatus, including the microfluidic chip, was sequentially subjected to airtightness testing and vacuuming.

[0029] The internal temperature of the microfluidic chip is raised to the temperature of the target gas reservoir. Formation water containing dissolved gas is injected into the microfluidic chip. Before injection, the experimental confining pressure is controlled to be higher than the injection pressure of the formation water containing dissolved gas. Throughout the experiment, the confining pressure is kept higher than the pressure at both ends of the microfluidic chip. After injection, the pressure at both ends of the microfluidic chip is raised to the pressure of the target gas reservoir, and the experimental fluid is allowed to fully saturate the microfluidic chip.

[0030] Preferably, in the above-mentioned method for measuring the overall compressibility coefficient of formation water, the formation water depletion development experiment based on a microfluidic chip under in-situ reservoir conditions includes:

[0031] The pressure at both ends of the microfluidic chip is reduced by the same amount. The change in gas-water saturation in the porous region inside the microfluidic chip under the corresponding pressure is observed and recorded. After the gas-water saturation stabilizes, the pressure at both ends of the microfluidic chip is controlled to continue to be reduced synchronously.

[0032] Repeat the previous step until the experimental preset pressure is reached. After the last set of records is completed, the experiment ends and the experimental system is depressurized.

[0033] Preferably, in the above-mentioned method for measuring the overall compressibility coefficient of formation water, the step of recording the gas-water saturation and pressure changes within the microfluidic chip includes:

[0034] The original video of the microfluidic experiment was converted into an image sequence and imported into image processing software. The images were then converted to grayscale, and histogram equalization and contrast enhancement methods were used to optimize the image quality. Median filtering or bilateral filtering was used to remove background interference.

[0035] Gas phase regions are extracted using threshold segmentation methods or edge detection algorithms, and the extraction results are optimized by combining morphological operations. For complex flow states, deep learning methods are used for gas phase recognition.

[0036] The number of pixels in the gas phase region is calculated, and the gas-water saturation at different spatial scales is derived by combining the porosity parameters of the chip matrix. By analyzing the changes in the gas phase region during the depressurization process, the curve of gas phase saturation changing with pressure is plotted.

[0037] Preferably, in the above-mentioned method for measuring the overall compressibility coefficient of formation water, the step of quantifying the change in the volume of precipitated gas bubbles with pressure drop using image analysis software and calculating the first compressibility coefficient contributed by the dissolved gas portion includes:

[0038] Using formula Calculate the first compression factor;

[0039] Among them, C g V is the first compression coefficient, V is the volume of the porous medium region inside the chip, V0 is the gas phase volume under the initial conditions, V1 is the gas phase volume under the current conditions, P0 is the pressure under the initial conditions, and P1 is the pressure under the current conditions.

[0040] Preferably, in the above-mentioned method for measuring the overall compressibility coefficient of formation water, the step of theoretically calculating the compressibility coefficient of the formation water itself, based on experimental conditions, to obtain the second compressibility coefficient contributed by the formation water itself includes:

[0041] Using formula Calculate the second compression factor;

[0042] Among them, C w B0 is the second compressibility coefficient, B1 is the pure water volume coefficient under the initial conditions, and B1 is the pure water volume coefficient under the current conditions.

[0043] Preferably, in the above-mentioned method for measuring the overall compressibility coefficient of formation water, the step of superimposing the first compressibility coefficient and the second compressibility coefficient to obtain the overall isothermal compressibility coefficient of formation water includes:

[0044] Using formula The overall isothermal compressibility coefficient of the formation water was obtained;

[0045] Among them, C 综合 C is the comprehensive isothermal compressibility coefficient of the formation water. wC is the second compression factor. g is the first compression coefficient.

[0046] The present invention provides a formation water comprehensive compressibility coefficient measurement system comprising:

[0047] The extraction module is used to extract the distribution pattern of fracture networks and pore structure parameters based on the reservoir characteristics of the target gas reservoir.

[0048] A fabrication module is used to fabricate a microfluidic chip having the aforementioned crack network distribution pattern and pore structure parameters;

[0049] The formation water fluid configuration module is used to obtain the composition of the formation water in the target gas reservoir and configure a formation water fluid containing dissolved gas.

[0050] The imaging and recording module is used to conduct formation water depletion development experiments under in-situ reservoir conditions based on a microfluidic chip, and to capture and record the gas-water saturation and pressure changes within the microfluidic chip.

[0051] The first calculation module is used to quantify the change in the volume of precipitated bubbles with pressure drop through image analysis software, and to calculate the first compressibility coefficient contributed by the dissolved gas portion.

[0052] The second calculation module is used to perform theoretical calculations on the compressibility coefficient of the formation water body in combination with experimental conditions, and to obtain the second compressibility coefficient contributed by the formation water body.

[0053] The third calculation module is used to superimpose the first compression coefficient and the second compression coefficient to obtain the comprehensive isothermal compression coefficient of formation water.

[0054] As described above, the formation water comprehensive compressibility measurement method provided by this invention includes: extracting fracture network distribution patterns and pore structure parameters based on the characteristics of the target gas reservoir; preparing a microfluidic chip with the fracture network distribution patterns and pore structure parameters; obtaining the composition of the formation water in the target gas reservoir, configuring a formation water fluid containing dissolved gas, and injecting the formation water fluid containing dissolved gas into the microfluidic chip; conducting a formation water depletion development experiment under in-situ reservoir conditions based on the microfluidic chip, and recording the gas-water saturation and pressure changes within the microfluidic chip; quantifying the change in bubble volume with pressure drop using image analysis software, and calculating the first compressibility coefficient contributed by the dissolved gas portion; and, in conjunction with the experimental conditions, further optimizing the compressibility coefficient of the formation water itself. Theoretical calculations are performed to obtain the second compressibility coefficient contributed by the formation water itself. The first and second compressibility coefficients are then superimposed to obtain the overall isothermal compressibility coefficient of formation water. This allows for a more accurate simulation of the microscopic pore structure, fracture network, and fluid flow behavior of fractured low-porosity sandstone gas reservoirs, realistically reflecting the depletion and development process at the microscopic scale. Furthermore, it effectively simulates the impact of reservoir heterogeneity on fluid flow and provides a theoretical basis for subsequent formation energy replenishment by simulating the depletion and development process, thereby improving gas recovery. It also enables real-time dynamic monitoring of the formation water gas evolution and expansion process, and, combined with changes in gas-water saturation and pressure, more accurately calculates the overall isothermal compressibility coefficient of formation water, improving gas reservoir development efficiency and facilitating the development and evaluation of complex reservoirs. The formation water overall compressibility coefficient measurement system provided by this invention has the same advantages as the aforementioned formation water overall compressibility coefficient measurement method. Attached Figure Description

[0055] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0056] Figure 1 This is a schematic diagram of an embodiment of a method for measuring the overall compressibility coefficient of formation water provided by the present invention;

[0057] Figure 2 This is a schematic diagram of an embodiment of a formation water comprehensive compressibility coefficient measurement system provided by the present invention. Detailed Implementation

[0058] The core of this invention is to provide a method and system for measuring the comprehensive compressibility coefficient of formation water. This method can more accurately simulate the microscopic pore structure, fracture network, and fluid flow behavior of fractured low-porosity sandstone gas reservoirs, realistically reflecting the depletion and development process of fractured low-porosity sandstone gas reservoirs at the microscopic scale. It can also effectively simulate the impact of reservoir heterogeneity on fluid flow and provide a theoretical basis for subsequent formation energy replenishment by simulating the depletion and development process, thereby improving the gas recovery rate. Furthermore, it can monitor the formation water gas expansion process in real time and, combined with changes in gas-water saturation and pressure, more accurately calculate the comprehensive isothermal compressibility coefficient of formation water, thereby improving gas reservoir development efficiency and being more conducive to the development and evaluation of complex reservoirs.

[0059] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0060] An example implementation of the method for measuring the overall compressibility coefficient of formation water provided by this invention. Figure 1 As shown, Figure 1 This is a schematic diagram of an embodiment of a method for measuring the overall compressibility coefficient of formation water provided by the present invention. The method may include the following steps:

[0061] S1: Based on the characteristics of the target gas reservoir, extract the distribution pattern of fracture network and pore structure parameters;

[0062] It should be noted that the distribution pattern of the fracture network can include fracture development characteristics, fracture distribution model and fractal characteristics, and pore structure parameters can include pore type, pore network model and fracture porosity and permeability, which can be extracted by methods such as field outcrops, core analysis, CT scan, experimental testing (such as high pressure mercury intrusion) and three-dimensional random modeling.

[0063] S2: Fabrication of microfluidic chips with crack network distribution patterns and pore structure parameters;

[0064] Specifically, in order to replicate the fracture network distribution and pore structure parameters of real gas reservoirs onto a two-dimensional microfluidic chip, the following five-step closed-loop preparation process can be adopted to ensure that the geometric scale and flow characteristics are consistent with the original core: three-dimensional digital core acquisition, multi-scale parameter dimensionality reduction mapping, mask layout drawing and precision control, chip micromachining, and structural verification and dynamic calibration. Through the above process, a multi-scale real core model containing "fracture main channels + matrix pore network" can be constructed on a 30mm×15mm chip.

[0065] S3: Obtain the composition of formation water in the target gas reservoir, prepare formation water fluid containing dissolved gas, and inject the formation water fluid containing dissolved gas into the microfluidic chip.

[0066] Specifically, the composition of the formation water in the target gas reservoir can be obtained based on the formation water composition analysis data of the target gas reservoir. Then, dissolved gases, including natural gas, are dissolved in the formation water. The water fluid containing dissolved gases is then injected into the microfluidic chip. In this way, an environment containing dissolved gases and formation water that is consistent with the in-situ conditions of the target gas reservoir can be established in the microfluidic chip for subsequent percolation, displacement, or scaling experiments.

[0067] S4: Based on the microfluidic chip, conduct formation water depletion development experiments under in-situ reservoir conditions, and record the gas-water saturation and pressure changes within the microfluidic chip.

[0068] Specifically, it can record the curves of gas / water saturation in the fracture-pore network as the average pressure decreases, obtain the morphology of the dissolved gas displacement front, the entire process of bubble nucleation-aggregation-migration, and simultaneously measure the pressure at three points: inlet, outlet, and fracture, and establish pressure drop-saturation-time coupled data.

[0069] S5: The change in the volume of precipitated bubbles with pressure drop is quantified using image analysis software, and the first compressibility coefficient contributed by the dissolved gas is calculated.

[0070] It should be noted that this step requires converting the image information into a quantitative chain of "bubble volume change" → "gas mass change" → "dissolved gas compressibility coefficient". This allows the true first compressibility coefficient contributed by the dissolved gas portion to be obtained directly from the microfluidic visualization experiment, providing high-pressure experimental basis for the equilibrium calculation and numerical simulation of gas reservoir materials.

[0071] S6: Based on the experimental conditions, the compressibility coefficient of the formation water body is theoretically calculated to obtain the second compressibility coefficient contributed by the formation water body.

[0072] Specifically, this step allows us to obtain the contribution of the formation water mass to the compressibility coefficient.

[0073] S7: The first and second compressibility coefficients are superimposed to obtain the comprehensive isothermal compressibility coefficient of formation water.

[0074] It is evident that this scheme fully considers the influence of formation water on the compressibility coefficient and the influence of dissolved gas on the compressibility coefficient, thus making the final result more accurate.

[0075] As described above, the embodiments of the formation water comprehensive compressibility coefficient measurement method provided by the present invention include: extracting fracture network distribution patterns and pore structure parameters based on the characteristics of the target gas reservoir; preparing a microfluidic chip with fracture network distribution patterns and pore structure parameters; obtaining the composition of formation water in the target gas reservoir, configuring formation water fluid containing dissolved gas, and injecting the formation water fluid containing dissolved gas into the microfluidic chip; conducting formation water depletion development experiments under in-situ reservoir conditions based on the microfluidic chip, and recording the gas-water saturation and pressure changes within the microfluidic chip; quantifying the change in bubble volume with pressure drop using image analysis software, and calculating the first compressibility coefficient contributed by the dissolved gas portion; and theoretically calculating the bulk compressibility coefficient of the formation water based on the experimental conditions. The calculation yields the second compressibility coefficient contributed by the formation water itself. The first and second compressibility coefficients are then superimposed to obtain the comprehensive isothermal compressibility coefficient of the formation water. This allows for a more accurate simulation of the microscopic pore structure, fracture network, and fluid flow behavior of fractured low-porosity sandstone gas reservoirs. It realistically reflects the depletion and development process of fractured low-porosity sandstone gas reservoirs at the microscopic scale. Furthermore, it effectively simulates the impact of reservoir heterogeneity on fluid flow and provides a theoretical basis for subsequent formation energy replenishment by simulating the depletion and development process, thereby improving the gas recovery rate. It also enables real-time dynamic monitoring of the formation water gas expansion process and, combined with changes in gas-water saturation and pressure, more accurately calculates the comprehensive isothermal compressibility coefficient of the formation water, improving gas reservoir development efficiency and facilitating the development and evaluation of complex reservoirs.

[0076] In a specific embodiment of the above-mentioned method for measuring the overall compressibility coefficient of formation water, extracting the fracture network distribution pattern and pore structure parameters based on the characteristics of the target gas reservoir may include:

[0077] Porosity tests were performed on dry core samples from the target gas reservoir to obtain the reservoir's porosity parameters, which can then be used to design microfluidic chips.

[0078] High-pressure mercury intrusion testing was performed on dry core samples. Mercury was injected into the pores of the dry core samples under high pressure, and the size distribution of the pores was measured to obtain detailed pore throat structure information, providing pore radius parameters for the design of microfluidic chips.

[0079] Structural scanning of dry core samples from the target gas reservoir can be performed using techniques such as computed tomography, focused ion beam scanning electron microscopy, or nuclear magnetic resonance imaging to obtain a true pore structure map of the dry core sample.

[0080] The pore structure map is binarized to obtain a pore distribution image. The pore structure features are statistically analyzed, and representative pore morphologies are selected as design parameters for the reservoir pore morphology of the microfluidic chip.

[0081] It should be noted that the above steps can not only determine the size and volume of pores, but also establish the basis for reservoir pore morphology design. In other words, they can determine the morphology of pores. Combining these two aspects, we can design pores that are more in line with reality.

[0082] In another specific implementation of the above-mentioned method for measuring the overall compressibility coefficient of formation water, based on the above-mentioned embodiments, the preparation of the microfluidic chip with fracture network distribution law and pore structure parameters can specifically include:

[0083] Based on porosity parameters, pore radius parameters, and representative pore morphologies, random reconstruction is performed in the porous medium region of the microfluidic chip structure, allowing for scaling and other operations on the pore morphology.

[0084] To reflect the real pore-throat structure, throats are generated using the Thiessen polygon algorithm or self-organizing map neural network algorithm based on random reconstruction, so that the pores can be connected by throats. The coordination number of each pore and the number of throats are set. The resulting microfluidic chip structure is then imported into CAD software for use in subsequent microfluidic chip fabrication steps.

[0085] Based on the above microfluidic chip structure, the microfluidic chip is prepared by sequentially performing the following steps: coating, photolithography, development, etching, resist removal, etching, bonding, and wetting. Of course, these steps can also be fine-tuned, and there are no restrictions here.

[0086] In another specific embodiment of the above-mentioned method for measuring the overall compressibility coefficient of formation water, based on the above embodiment, the composition of the formation water in the target gas reservoir is obtained, a formation water fluid containing dissolved gas is prepared, and the injection of the formation water fluid containing dissolved gas into the microfluidic chip may include the following steps:

[0087] Analyze the gas composition of the target gas reservoir and prepare an equal proportion of gas as the experimental gas. The specific analysis can be based on the gas composition analysis data of the target gas reservoir.

[0088] Analyze the formation water composition and related mineralization standards of the target gas reservoir, and prepare brine with the corresponding mineralization as the experimental liquid. Specifically, the experimental liquid can be prepared according to the formation water composition analysis data and related mineralization standards of the target gas reservoir.

[0089] The experimental gas and experimental liquid are mixed in an intermediate container, and the pressure is increased to dissolve all the experimental gas into the experimental liquid, forming a formation water fluid containing dissolved gas.

[0090] The experimental setup, including the microfluidic chip, was subjected to airtightness testing and vacuuming in sequence.

[0091] The internal temperature of the microfluidic chip can be raised to the temperature of the target gas reservoir by means of electromagnetic heating, etc. Formation water containing dissolved gas is injected into the microfluidic chip. Before injection, the experimental confining pressure is controlled to be higher than the injection pressure of the formation water containing dissolved gas. Throughout the experiment, the confining pressure must be kept higher than the pressure at both ends of the microfluidic chip. After injection, the pressure at both ends of the microfluidic chip is raised to the pressure of the target gas reservoir, and the experimental fluid is allowed to fully saturate the microfluidic chip.

[0092] In a preferred embodiment of the above-described method for measuring the overall compressibility coefficient of formation water, based on the above embodiment and using a microfluidic chip, the formation water depletion development experiment under in-situ reservoir conditions may include the following steps:

[0093] Reduce the pressure at both ends of the microfluidic chip by the same amount, observe and record the change in gas-water saturation in the porous region inside the microfluidic chip under the corresponding pressure, and after the gas-water saturation stabilizes, control the pressure at both ends of the microfluidic chip to continue to decrease synchronously.

[0094] Repeat the previous step until the experimental preset pressure is reached. After the last set of records is completed, the experiment ends and the experimental system is depressurized.

[0095] In another preferred embodiment of the above-mentioned method for measuring the overall compressibility coefficient of formation water, based on the above embodiment, recording the gas-water saturation and pressure changes within the microfluidic chip may specifically include:

[0096] The original video of the microfluidic experiment was converted into an image sequence and imported into image processing software, such as ImageJ, Matlab or Python OpenCV. The images were then converted to grayscale and histogram equalization and contrast enhancement methods were used to optimize the image quality. Median filtering or bilateral filtering was used to remove background interference in order to improve the identification accuracy of gas phase and water phase.

[0097] Gas phase regions are extracted using threshold segmentation methods (such as Otsu thresholding and adaptive thresholding) or edge detection algorithms (such as Canny and Sobel operators), and the extraction results are optimized by combining morphological operations (such as erosion, expansion, and opening / closing operations) to ensure the clarity and accuracy of gas phase boundaries. For complex flow regimes, deep learning methods (such as U-Net and Mask R-CNN) can be used for gas phase recognition to improve adaptability to different bubble morphologies.

[0098] The number of pixels in the gas phase region is calculated, and the gas-water saturation at different spatial scales is derived by combining the porosity parameters of the chip matrix. By analyzing the changes in the gas phase region during the depressurization process, the curve of gas phase saturation as a function of pressure is plotted.

[0099] In another preferred embodiment of the above-mentioned method for measuring the overall compressibility coefficient of formation water, based on the above embodiment, the change in the volume of precipitated bubbles with pressure drop is quantified using image analysis software, and the first compressibility coefficient contributed by the dissolved gas portion is calculated. Specifically, this may include:

[0100] Using formula Calculate the first compression factor;

[0101] Among them, C g V is the first compression factor, V is the volume of the porous medium region inside the chip, V0 is the gas phase volume under the initial conditions, V1 is the gas phase volume under the current conditions, P0 is the pressure under the initial conditions, and P1 is the pressure under the current conditions.

[0102] It should be noted that the initial conditions here refer to the temperature and pressure conditions of the chip at the beginning of the experiment. Under these initial conditions, the inside of the chip is entirely liquid, and the gas is dissolved in the water. As for the current conditions, since the experiment is a depressurization process, the current conditions are the temperature and pressure conditions at a certain pressure. As the pressure decreases, the gas will be released from the water. Based on the curve of gas phase saturation changing with pressure and the physical information of the microfluidic chip, the corresponding V, V0, and V1 can be calculated.

[0103] Furthermore, based on the above embodiments and combined with experimental conditions, the compressibility coefficient of the formation water volume is theoretically calculated, and the second compressibility coefficient contributed by the formation water volume can specifically include:

[0104] Using formula Calculate the second compression factor;

[0105] Among them, C w B0 is the second compressibility factor, B1 is the pure water volume factor under the initial conditions, and B1 is the pure water volume factor under the current conditions.

[0106] It should be noted that C w The formation water volume factor at the corresponding temperature and pressure can be found in the NIST database and substituted into the formula for calculation.

[0107] Furthermore, the superposition of the first and second compressibility coefficients to obtain the overall isothermal compressibility coefficient of formation water may include the following steps:

[0108] Using formula The overall isothermal compressibility coefficient of formation water was obtained;

[0109] Among them, C 综合 C is the comprehensive isothermal compressibility coefficient of formation water. w C is the second compression factor. g This is the first compression factor.

[0110] In this case, the comprehensive isothermal compressibility coefficient curves of gas-bearing formation water under different pressures can be plotted.

[0111] In summary, the above-mentioned method for measuring the comprehensive compressibility coefficient of formation water first constructs a microphysical model of fractured low-porosity sandstone gas reservoirs. This is achieved by analyzing the porosity, permeability, and micropore structure of reservoir cores, combined with fracture combination patterns, to determine the design parameters of the microphysical model. Based on pore size distribution statistics, characteristic peak values ​​and proportions are selected to form a multi-scale coupled microscopic visualization physical model design chart, and the microphysical model is prepared. The actual core is then scanned using computed tomography, focused ion beam scanning electron microscopy, or nuclear magnetic resonance imaging (NMR) to obtain pore structure maps, which are then binarized. Representative pore morphologies are selected as design parameters, and throats are generated using the Thiessen polygon algorithm and self-organizing map neural network algorithm to reflect the actual pore-throat structure. Finally, a formation water depletion development experiment is conducted. Under in-situ reservoir conditions, the microphysical model is used to carry out the formation water depletion development experiment, observing and recording the formation water gas evolution and expansion process in real time. By providing confining and regulating pressure using an IS-CO pump, formation water is injected into the porous media region within the microphysical model to perform depressurization, simulating the process of gas reservoir depletion and development. Finally, the changes in gas-water saturation and the comprehensive isothermal compressibility coefficient are calculated. Microscopic imaging technology is used to observe the gas-water distribution within the microphysical model, and image processing software is used to process the images, extract the gas phase region, and calculate the changes in gas-water saturation. Based on the curve of gas phase saturation changing with pressure and the physical information of the microphysical model, the comprehensive isothermal compressibility coefficient of the gas-bearing formation water is calculated, and the comprehensive isothermal compressibility coefficient curves under different pressures are plotted.

[0112] The aforementioned method can realistically simulate the depletion and development process of fractured low-porosity sandstone gas reservoirs. By constructing a microscopic physical model and combining fracture combination patterns and pore structure characteristics, it can accurately simulate the microscopic pore structure and fluid flow behavior of the gas reservoir. Formation water depletion development experiments can be conducted under in-situ reservoir conditions, and the formation water gas expansion process can be observed in real time. This solves the problem that existing technologies cannot fully reflect the fluid seepage characteristics of fractured low-porosity sandstone gas reservoirs at the micro- and nanoscale, providing strong support for optimizing gas reservoir development schemes. Through microscopic imaging techniques and image processing methods, the gas-water distribution within the microscopic physical model can be accurately observed, and changes in gas-water saturation can be calculated. Combined with pressure changes and using specific calculation formulas, the comprehensive isothermal compressibility coefficient of formation water can be accurately calculated, overcoming the limitations of existing technologies in measuring the comprehensive isothermal compressibility coefficient of formation water. This provides crucial evidence for evaluating the elastic drive effect and improving the development efficiency of gas reservoirs.

[0113] The above method can realistically simulate the high temperature and high pressure conditions of fractured low-porosity sandstone gas reservoirs, and can measure the gas contribution of the formation water comprehensive isothermal compressibility coefficient. Its principle is clear and reliable, and the operation method is simple. It constructs precise nanoscale pores through nanofluid control technology, and realizes the simulation of depletion development of fractured low-porosity sandstone gas reservoirs and the measurement of the formation water comprehensive isothermal compressibility coefficient. It solves the problem that existing technologies cannot fully reflect the fluid seepage and fluid characteristics of fractured low-porosity sandstone gas reservoirs at the micro- and nanoscale.

[0114] An example implementation of the formation water integrated compressibility coefficient measurement system provided by the present invention Figure 2 As shown, Figure 2 This is a schematic diagram of an embodiment of a formation water integrated compressibility coefficient measurement system provided by the present invention. The system may include:

[0115] The extraction module 201 is used to extract the fracture network distribution pattern and pore structure parameters based on the characteristics of the target gas reservoir. It should be noted that the fracture network distribution pattern can include fracture development characteristics, fracture distribution model and fractal characteristics, and the pore structure parameters can include pore type, pore network model and fracture porosity and permeability. These parameters can be extracted through methods such as field outcrops, core analysis, CT scan, experimental testing (such as high pressure mercury intrusion) and three-dimensional random modeling.

[0116] The preparation module 202 is used to prepare a microfluidic chip with fracture network distribution patterns and pore structure parameters. Specifically, in order to replicate the fracture network distribution patterns and pore structure parameters in the real gas reservoir into the two-dimensional microfluidic chip, the following five-step closed-loop preparation process can be adopted to ensure that the geometric scale and flow characteristics are statistically consistent with the original core: three-dimensional digital core acquisition, multi-scale parameter dimensionality reduction mapping, mask layout drawing and precision control, chip micromachining, and structural verification and dynamic calibration. Through the above process, a multi-scale real core model containing "fracture main channel + matrix pore network" can be constructed on a 30mm×15mm chip.

[0117] The formation water fluid configuration module 203 is used to obtain the composition of the formation water in the target gas reservoir and configure the formation water fluid containing dissolved gas. Specifically, the composition of the formation water in the target gas reservoir can be obtained based on the formation water composition analysis data of the target gas reservoir. Then, dissolved gas, including natural gas, is dissolved in the formation water. The water fluid containing dissolved gas is then injected into the microfluidic chip. In this way, a formation water environment containing dissolved gas that is consistent with the in-situ conditions of the target gas reservoir can be established in the microfluidic chip for subsequent percolation, displacement or scaling experiments.

[0118] The imaging and recording module 204 is used to conduct formation water depletion development experiments in in-situ reservoir conditions based on microfluidic chips. It records the gas and water saturation and pressure changes within the microfluidic chip. Specifically, it can record the curve of gas / water saturation in the fracture-pore network as the average pressure decreases, obtain the morphology of the dissolved gas displacement front, the entire process of bubble nucleation-aggregation-migration, and synchronously measure the pressure at three points: inlet, outlet, and fracture, and establish coupled data of pressure drop, saturation, and time.

[0119] The first calculation module 205 is used to quantify the change in bubble volume with pressure drop through image analysis software and calculate the first compressibility coefficient contributed by the dissolved gas. It should be noted that the image information needs to be converted into a quantitative chain of "bubble volume change" → "gas mass change" → "dissolved gas compressibility coefficient". The true first compressibility coefficient contributed by the dissolved gas can be obtained directly from the microfluidic visualization experiment, providing a high-pressure experimental basis for gas reservoir material balance calculation and numerical simulation.

[0120] The second calculation module 206 is used to perform theoretical calculations on the compressibility coefficient of the formation water body in combination with experimental conditions, and to obtain the second compressibility coefficient contributed by the formation water body. Specifically, this allows us to obtain the contribution value of the formation water body to the compressibility coefficient.

[0121] The third calculation module 207 is used to superimpose the first compressibility coefficient and the second compressibility coefficient to obtain the comprehensive isothermal compressibility coefficient of formation water. It can be seen that this fully considers the influence of the formation water itself on the compressibility coefficient and the influence of dissolved gas on the compressibility coefficient, thus making the result more accurate.

[0122] In summary, the aforementioned formation water comprehensive compressibility coefficient measurement system can more accurately simulate the microscopic pore structure, fracture network, and fluid flow behavior of fractured low-porosity sandstone gas reservoirs. It realistically reflects the depletion and development process of fractured low-porosity sandstone gas reservoirs at the microscopic scale. Furthermore, it can effectively simulate the impact of reservoir heterogeneity on fluid flow and provide a theoretical basis for subsequent formation energy replenishment by simulating the depletion and development process, thereby improving the gas recovery rate. It can also dynamically monitor the formation water gas expansion process in real time and, combined with changes in gas-water saturation and pressure, more accurately calculate the comprehensive isothermal compressibility coefficient of formation water, improving gas reservoir development efficiency and facilitating the development and evaluation of complex reservoirs.

[0123] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for measuring the overall compressibility coefficient of formation water, characterized in that, include: Based on the characteristics of the target gas reservoir, the distribution pattern of fracture network and pore structure parameters are extracted. A microfluidic chip with the aforementioned crack network distribution pattern and pore structure parameters was prepared. The composition of formation water in the target gas reservoir is obtained, a formation water fluid containing dissolved gas is prepared, and the formation water fluid containing dissolved gas is injected into the microfluidic chip. Based on the microfluidic chip, a formation water depletion development experiment was conducted under in-situ reservoir conditions, and the gas-water saturation and pressure changes within the microfluidic chip were recorded. The change in the volume of precipitated bubbles with pressure drop was quantified using image analysis software, and the first compressibility coefficient contributed by the dissolved gas was calculated. Based on experimental conditions, the compressibility coefficient of the formation water volume was theoretically calculated, and the second compressibility coefficient contributed by the formation water volume was obtained. The first compressibility coefficient and the second compressibility coefficient are superimposed to obtain the comprehensive isothermal compressibility coefficient of formation water.

2. The method for measuring the comprehensive compressibility coefficient of formation water according to claim 1, characterized in that, The extraction of fracture network distribution patterns and pore structure parameters based on the characteristics of the target gas reservoir includes: Porosity tests were performed on dry core samples from the target gas reservoir to obtain the reservoir's porosity parameters. High-pressure mercury intrusion testing was performed on the dried core. Mercury was injected into the pores of the dried core under high pressure, and the size distribution of the pores was measured to obtain detailed pore throat structure information, providing pore radius parameters for the design of the microfluidic chip. Structural scanning was performed on the dry core of the target gas reservoir to obtain a pore structure map of the interior of the dry core; The pore structure image is binarized to obtain a pore distribution image. The pore structure features are statistically analyzed, and representative pore morphologies are selected.

3. The method for measuring the comprehensive compressibility coefficient of formation water according to claim 2, characterized in that, The fabrication of the microfluidic chip having the aforementioned crack network distribution pattern and pore structure parameters includes: Based on the porosity parameter, the pore radius parameter, and the representative pore morphology, random reconstruction is performed in the porous medium region of the microfluidic chip structure; Based on random reconstruction, throats are generated using the Thiessen polygon algorithm or self-organizing map neural network algorithm to connect the pores using throats. The coordination number and number of throats for each pore are set, and the resulting microfluidic chip structure is imported into CAD software. Based on the microfluidic chip structure, the microfluidic chip is prepared by sequentially performing the following steps: coating, photolithography, development, etching, resist removal, etching, bonding, and wetting.

4. The method for measuring the comprehensive compressibility coefficient of formation water according to claim 3, characterized in that, The steps of obtaining the composition of formation water in the target gas reservoir, preparing a formation water fluid containing dissolved gas, and injecting the formation water fluid containing dissolved gas into the microfluidic chip include: Analyze the gas composition of the target gas reservoir and prepare an equal proportion of gas as experimental gas; The formation water composition and related mineralization standards of the target gas reservoir were analyzed, and brine with the corresponding mineralization was prepared as the experimental liquid. The experimental gas and the experimental liquid are mixed in an intermediate container, and the pressure is increased to dissolve all the experimental gas into the experimental liquid, forming the formation water fluid containing dissolved gas. The experimental apparatus, including the microfluidic chip, was sequentially subjected to airtightness testing and vacuuming. The internal temperature of the microfluidic chip is raised to the temperature of the target gas reservoir. Formation water containing dissolved gas is injected into the microfluidic chip. Before injection, the experimental confining pressure is controlled to be higher than the injection pressure of the formation water containing dissolved gas. Throughout the experiment, the confining pressure is kept higher than the pressure at both ends of the microfluidic chip. After injection, the pressure at both ends of the microfluidic chip is raised to the pressure of the target gas reservoir, and the experimental fluid is allowed to fully saturate the microfluidic chip.

5. The method for measuring the overall compressibility coefficient of formation water according to claim 4, characterized in that, The formation water depletion development experiment based on microfluidic chips under in-situ reservoir conditions includes: The pressure at both ends of the microfluidic chip is reduced by the same amount. The change in gas-water saturation in the porous region inside the microfluidic chip under the corresponding pressure is observed and recorded. After the gas-water saturation stabilizes, the pressure at both ends of the microfluidic chip is controlled to continue to be reduced synchronously. Repeat the previous step until the experimental preset pressure is reached. After the last set of records is completed, the experiment ends and the experimental system is depressurized.

6. The method for measuring the overall compressibility coefficient of formation water according to claim 5, characterized in that, The recording of gas-water saturation and pressure changes within the microfluidic chip includes: The original video of the microfluidic experiment was converted into an image sequence and imported into image processing software. The images were then converted to grayscale, and histogram equalization and contrast enhancement methods were used to optimize the image quality. Median filtering or bilateral filtering was used to remove background interference. Gas phase regions are extracted using threshold segmentation methods or edge detection algorithms, and the extraction results are optimized by combining morphological operations. For complex flow states, deep learning methods are used for gas phase recognition. The number of pixels in the gas phase region is calculated, and the gas-water saturation at different spatial scales is derived by combining the porosity parameters of the chip matrix. By analyzing the changes in the gas phase region during the depressurization process, the curve of gas phase saturation changing with pressure is plotted.

7. The method for measuring the comprehensive compressibility coefficient of formation water according to claim 6, characterized in that, The first compressibility coefficient, calculated by quantifying the change in the volume of precipitated bubbles with pressure drop using image analysis software, includes the contribution of the dissolved gas portion: Using formula Calculate the first compression factor; Among them, C g V is the first compression coefficient, V is the volume of the porous medium region inside the chip, V0 is the gas phase volume under the initial conditions, V1 is the gas phase volume under the current conditions, P0 is the pressure under the initial conditions, and P1 is the pressure under the current conditions.

8. The method for measuring the comprehensive compressibility coefficient of formation water according to claim 7, characterized in that, Based on the experimental conditions, the compressibility coefficient of the formation water volume was theoretically calculated, and the second compressibility coefficient contributed by the formation water volume was obtained, including: Using formula Calculate the second compression factor; Among them, C w B0 is the second compressibility coefficient, B1 is the pure water volume coefficient under the initial conditions, and B1 is the pure water volume coefficient under the current conditions.

9. The method for measuring the comprehensive compressibility coefficient of formation water according to claim 8, characterized in that, The step of superimposing the first compressibility coefficient and the second compressibility coefficient to obtain the overall isothermal compressibility coefficient of formation water includes: Using formula The overall isothermal compressibility coefficient of the formation water was obtained; Among them, C 综合 C is the comprehensive isothermal compressibility coefficient of the formation water. w C is the second compression factor. g is the first compression coefficient.

10. A system for measuring the overall compressibility coefficient of formation water, characterized in that, include: The extraction module is used to extract the distribution pattern of fracture networks and pore structure parameters based on the reservoir characteristics of the target gas reservoir. A fabrication module is used to fabricate a microfluidic chip having the aforementioned crack network distribution pattern and pore structure parameters; The formation water fluid configuration module is used to obtain the composition of the formation water in the target gas reservoir and configure a formation water fluid containing dissolved gas. The imaging and recording module is used to conduct formation water depletion development experiments under in-situ reservoir conditions based on a microfluidic chip, and to capture and record the gas-water saturation and pressure changes within the microfluidic chip. The first calculation module is used to quantify the change in the volume of precipitated bubbles with pressure drop through image analysis software, and to calculate the first compressibility coefficient contributed by the dissolved gas portion. The second calculation module is used to perform theoretical calculations on the compressibility coefficient of the formation water body in combination with experimental conditions, and to obtain the second compressibility coefficient contributed by the formation water body. The third calculation module is used to superimpose the first compression coefficient and the second compression coefficient to obtain the comprehensive isothermal compression coefficient of formation water.

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