Hydrate dissociation method and system accounting for pressure wave time lag and pore structure entropy

Abstract

The present application relates to hydrate depressurization production numerical simulation technical field, specifically relates to hydrate decomposition method and system considering pressure wave time lag and pore structure entropy, the method includes the following steps: calculating pore structure entropy, constructing saturation and structure entropy dependent time memory kernel, combining decomposition rate threshold, pressure drop threshold, forming the decomposition front indicator function with prediction-correction mechanism;The time memory kernel, space-time inseparable causal kernel and threshold response function are subjected to space-time convolution operation, based on the decomposition front indicator function, an integral form of non-local memory hydrate decomposition rate model is established;The Peacley number is calculated by grid Darcy velocity, the scalar characteristic memory time is extended to the second-order symmetric anisotropic memory time tensor, the second-order tensor type memory variable is constructed and the evolution equation is established, the non-local memory hydrate decomposition rate model is coupled to the energy conservation equation and two-phase Darcy seepage pressure equation, and the decomposition result is obtained by iterative solution.

Description

Technical Field

[0001] This invention relates to the field of numerical simulation technology for hydrate depressurization mining, specifically to a method and system for hydrate decomposition that considers pressure wave time delay and pore structure entropy. Background Technology

[0002] The basic principle and decomposition kinetics of hydrate depressurization extraction: Natural gas hydrates (combustible ice) are solid crystalline substances distributed in deep-sea sediments or terrestrial permafrost. Depressurization extraction reduces the fluid pressure near the bottom of the well, causing the hydrates in the reservoir to decompose into methane gas and water. It is currently the most economical extraction method. The hydrate decomposition rate is the core parameter that determines the gas production efficiency and reservoir stability.

[0003] Currently, most hydrate decomposition kinetic models are derived from the Kim Bishnoi type rate equation, which has the following three basic assumptions: locality (decomposition depends only on the current pressure drop at that point), memorylessness (historical pressure fluctuations have no cumulative effect), and linearity (the rate is proportional to the pressure drop).

[0004] In recent years, numerous experimental and numerical studies both domestically and internationally have revealed the limitations of the above assumptions: Historical memory effect: During the decomposition of hydrates, the methane bubbles produced are retained in the pores, changing the local pressure field and mass transfer conditions. Even if the external pressure is restored, the retained bubbles will continue to affect the subsequent decomposition. Traditional memoryless models cannot describe this phenomenon.

[0005] Spatial nonlocality and pressure wave time lag: Although the propagation speed of pressure waves in reservoirs (approximately 1500 m / s) is much faster than the thermal diffusion speed, a measurable propagation time (0.5–2 seconds) still exists in kilometer-scale reservoirs. Therefore, pressure disturbances from afar do not arrive at the current point instantaneously, but rather after a propagation time lag. Traditional "simultaneity" spatial convolution models (such as classical nonlocal theory) neglect this time lag.

[0006] Nonlinear driving force and permeation threshold: Experiments show that the relationship between hydrate decomposition rate and pressure drop is not a simple linear one: when the pressure drop is very small, decomposition hardly occurs (a critical initiation pressure drop exists); after exceeding the critical value, the decomposition rate increases power-law (corresponding to the formation of interconnected bubble channels); further increasing the pressure drop, mass transfer limitation causes the rate to peak and then decay. This "permeation threshold" behavior originates from bubble connectivity and blockage at the pore scale.

[0007] The impact of pore structure heterogeneity: The pore structure (pore size distribution, connectivity, coordination number) of real hydrate reservoirs exhibits strong spatial heterogeneity. High disorder in the pore structure leads to more severe bubble retention, a stronger memory effect, and a lower critical start-up pressure drop. Existing models treat decomposition kinetic parameters as functions of macroscopic saturation, completely ignoring the stochastic influence of pore structure.

[0008] Convection-induced directional stretching of memory: When fluid flows in the reservoir, historical effects along the flow direction are transported further, causing memory time to exhibit anisotropy: memory decays more slowly along the flow direction and more rapidly in the vertical direction. Existing memory models are all isotropic.

[0009] Some existing technologies have attempted to improve hydrate decomposition kinetics, for example, by modifying phase equilibrium curves or adjusting depressurization control strategies, but these improvements are still based on the traditional local, memoryless, linear framework. Specifically: Some patents only corrected the empirical parameters of the phase equilibrium curves without changing the basic form of the decomposition rate equation, and therefore still could not describe the historical memory effect and spatial nonlocal interactions.

[0010] Other patents focus on mining test equipment or pressure reduction control methods (such as PID control), whose decomposition rate calculation still uses traditional linear formulas and does not introduce nonlinear driving and pore structure parameters.

[0011] The decomposition kinetic models used by mainstream international simulation software (such as TOUGH+Hydrate and CMGSTARS) are all variants of local, memoryless, linear models.

[0012] In summary, existing technologies for modeling the kinetics of hydrate decomposition have not yet solved key issues such as pressure wave time delay, nonlocal memory, nonlinearity of the permeability threshold, pore structure entropy regulation, and anisotropic convection memory. The lack of these physical processes leads to significant deviations between simulation results and field observations, which restricts the optimization of depressurization mining processes. Summary of the Invention

[0013] To address the shortcomings of existing methods and the needs of practical applications, this invention provides a hydrate decomposition method that considers pressure wave time delay and pore structure entropy, comprising the following steps: Pore ​​structure entropy is calculated using the pore size and coordination number distribution of reservoir cores and used as an intrinsic property of each numerical grid cell. A time memory kernel dependent on saturation and structure entropy is constructed, and combined with the decomposition rate threshold and pressure drop threshold, a decomposition front indicator function with a prediction-correction mechanism is formed to control the activation region of memory calculation. The time memory kernel, the spatiotemporally inseparable causal kernel, and the threshold response function are spatiotemporally convolved. Based on the decomposition front indicator function, an integral form nonlocal memory hydrate decomposition rate model is established. The Pecley number is calculated using the grid Darcy velocity, and the scalar characteristic memory time is extended to a second-order symmetric anisotropic memory time tensor. A second-order tensor-type memory variable is constructed, and an evolution equation is established. The decomposition rate is taken as the trace of the memory tensor to characterize the directional stretching effect of fluid convection on the memory effect. The nonlocal memory hydrate decomposition rate model is coupled to the energy conservation equation and the two-phase Darcy flow pressure equation, and the decomposition result is obtained by iterative solution using an explicit time-progression scheme.

[0014] Optionally, the calculation of pore structure entropy using the pore size distribution and coordination number distribution of reservoir cores satisfies:

[0015] in, This represents the entropy of the pore structure; the larger the value, the more disordered the pore structure. This represents the maximum pore size in the reservoir core pore size distribution. This represents the minimum pore size in the reservoir core pore size distribution. Indicates aperture as The normalized aperture probability density function at time satisfies , This represents the coordination number of pore nodes in a pore network, i.e., the number of throats connected to a given pore. Indicates the coordination number is The normalized probability distribution function satisfies 1.

[0016] Optionally, the construction saturation and structural entropy-dependent time memory kernel satisfies:

[0017]

[0018]

[0019] in, This represents a time-memory kernel function, used to characterize the hysteretic effect of pressure disturbances, decomposition states, or mass transfer processes at historical moments on the current hydrate decomposition rate. Indicates the current calculation time. This indicates the historical integration moment or the historical moment of action. Representing historical moments With the current moment The time interval between these intervals, i.e., the memory lag time. Indicates local hydrate saturation. Represents the entropy of pore structure. This represents the Mitag-Leffler function, used to describe the memory effect with fractional decay characteristics. Indicates local hydrate saturation and pore structure entropy The relevant fractional memory decay index, This represents the minimum value of the fractional memory decay exponent. This represents the maximum value of the fractional memory decay exponent. This represents the coefficient that indicates the influence of pore structure entropy on the fractional-order memory decay exponent, used to adjust the effect of pore structure disorder on memory decay characteristics. This represents the characteristic memory time related to local hydrate saturation Sh and pore structure entropy H. This represents the memory time of basic features, used to characterize the memory time scale under baseline conditions. This represents the moderating coefficient of local hydrate saturation on feature memory time. This represents the adjustment coefficient of pore structure entropy on feature memory time, used to characterize the effect of pore structure disorder on memory duration.

[0020] Optionally, the decomposition rate threshold and pressure drop threshold are combined to form a decomposition leading edge indicator function with a prediction-correction mechanism, satisfying:

[0021] in, This represents the decomposition leading edge indicator function, used to determine spatial position. At the present moment Is it in an active decomposition region that requires the use of a non-local memory decomposition model? This indicates the spatial location or grid cell location within the reservoir's numerical computation domain. Indicates the current calculation time. This represents the rate of change of local hydrate saturation over time, used to characterize the activity level of hydrate decomposition processes within that grid cell. This represents the decomposition rate threshold or saturation change rate threshold. When the local hydrate saturation change rate exceeds this threshold, the region is considered to have entered an active decomposition state. This represents the local pressure drop, typically expressed as the difference between the phase equilibrium pressure and the current pressure, and is used to characterize the intensity of the pressure drop drive. This represents the pressure drop threshold, which is the minimum pressure drop required to trigger significant hydrate decomposition or activate the memory model. This represents the neighborhood radius, used to include grid cells near the decomposition leading edge but not yet reaching the threshold into the memory computation region in advance. Indicates the current or predicted position of the hydrate decomposition front. Indicates the position of the decomposed leading edge. Centered on The spatial neighborhood range of the neighborhood radius; when any condition is satisfied... 1 indicates that the non-local memory decomposition model is enabled at this location; when none of the above conditions are met, 0 indicates that the non-local memory decomposition model is not enabled at this location.

[0022] Optionally, the spatiotemporally indivisible causal kernel satisfies:

[0023] in, Represents a spacetime indivisible causal kernel, used to describe historical moments. Source Pressure disturbances or decomposition at a given point drive the current moment ,Location Nonlocal effects on the hydrate decomposition process; This indicates the current spatial location or target grid location to be calculated. This indicates the location of the historical disturbance source or the location of the integral source point. Indicates the current calculation time. Indicates the historical integration moment. This represents the time lag in the propagation of historical source disturbances to the current moment. Indicates the target location relative to the source point location Spatial distance between them This represents the time resolution or time smoothing parameter, used to approximate a finite-width response near the arrival time of the pressure wave. Indicates pressure wave velocity. It represents the effective bulk modulus of porous media, used to characterize the equivalent compressive stiffness of reservoir framework, pore fluid, and hydrate mixture systems. This represents the equivalent mixed density of gas, water, hydrates, and sedimentary framework in a porous medium. Indicates the pressure diffusion coefficient. Indicates the reference space attenuation length or the reference nonlocal action length. The pressure diffusion coefficient is used to characterize the ability of pressure disturbances to diffuse in porous media. Indicates reservoir permeability, Indicates the dynamic viscosity of a fluid. Indicates reservoir porosity. This represents the combined compressibility or overall compressibility, including the equivalent compressibility of the pore fluid and the porous media framework. This represents the reference pressure diffusion coefficient, used to normalize the local pressure diffusion coefficient. Optionally, the threshold response function satisfies:

[0024]

[0025] in, This represents the threshold response function, used to describe the nonlinear response strength of the hydrate decomposition rate driven by the phase equilibrium pressure drop. It represents the dimensionless phase equilibrium distance or dimensionless pressure driving force, reflecting the degree to which the current pressure deviates from the hydrate phase equilibrium pressure. Represents the entropy of pore structure. This represents the critical initiation threshold related to pore structure entropy, when... If the threshold is less than or equal to this threshold, hydrate decomposition is considered insignificant or not effectively triggered. This represents the reference critical start-up threshold, i.e., the dimensionless critical pressure driving force under reference pore structure conditions. This represents the adjustment coefficient of pore structure entropy on the critical initiation threshold, used to characterize the influence of pore structure disorder on decomposition initiation conditions. Represents the normalization constant, such that , This indicates the inflection point of the threshold response function, when... Less than or equal to When the decomposition response increases with increasing pressure driving force, it exhibits a power-law growth; when Greater than At that time, due to factors such as mass transfer limitations, bubble blockage, or localized cooling, the response function enters the decay phase. This represents the fractional power-law exponent related to the pore structure entropy, used to describe the degree of nonlinearity in the growth of the decomposition response after exceeding a critical threshold. Indicates the baseline power law exponent. This indicates the degree to which the entropy of the pore structure modulates the power-law exponent. This represents the maximum reference value for pore structure entropy, used to normalize the pore structure entropy H. This represents the attenuation coefficient, used to control the attenuation when... Greater than The rate at which the back threshold response function decays as the pressure driving force continues to increase. Indicates the current temperature. This represents the phase equilibrium pressure corresponding to temperature T. This indicates the current pressure value.

[0026] Optionally, the nonlocal memory hydrate decomposition rate model satisfies:

[0027] in, Indicates local hydrate saturation. Represents the entropy of pore structure. This indicates the current spatial location or target grid location to be calculated. Indicates the current calculation time. Indicates spatial location At the present moment The rate of change in hydrate saturation at a given location is used to characterize the rate of hydrate decomposition at that location. This represents the decomposition leading edge indicator function, used to control whether the nonlocal memory decomposition model is enabled at this location. This represents the spatial computational domain or nonlocal integration region of the hydrate reservoir. This represents the spatial integral variable, i.e., the location of the historical source point of the nonlocal action. This represents the time-integral variable, i.e., the historical moments of action. This represents the time memory kernel function, used to describe the memory effect of historical decomposition on the current decomposition rate. Representing historical moments Spatial location Local hydrate saturation at the location, Indicates spatial location The entropy of the pore structure at that location, Represents a spacetime inseparable causal kernel function, used to describe the source point. Historical disturbances at a location, after propagation by pressure waves, have a time lag in affecting the location. The impact of the location Representing historical moments Spatial location The dimensionless phase equilibrium distance or pressure driving force at the location. Representing historical moments Spatial location The threshold response function modulated by the entropy of the pore structure. This indicates a joint integration over historical time and spatial source points.

[0028] Optionally, the scalar feature memory time is extended to a second-order symmetric anisotropic memory time tensor, a second-order tensor type memory variable is constructed, and an evolution equation is established. The decomposition rate is taken from the trace of the memory tensor, satisfying:

[0029]

[0030]

[0031] in, Indicates local hydrate saturation. Represents the entropy of pore structure. This represents the second-order anisotropic memory time tensor obtained by scalar feature memory time extension. Indicates the local hydrate saturation and pore structure entropy Determined scalar basic feature memory time, Represents the grid Peckley number, Indicates the reference Peckley number, used for grid Peckley numbers. Normalization was performed, and the extent to which convection enhanced the anisotropy of the memory time tensor was controlled. This represents the grid Darcy velocity vector or the apparent velocity vector of the pore fluid. This represents the square of the magnitude of the velocity vector v. Represents velocity vector Its tensor product with itself is used to construct a directional tensor that enhances the flow direction. This represents the unit direction tensor along the fluid flow direction, used to characterize the directional stretching of the memory effect in the mainstream direction. This represents a second-order symmetric tensor memory variable used to record anisotropic memory states formed by the combined effects of historical pressure perturbations, decomposition drives, and fluid convection. This represents the rate of change of the second-order tensor memory variable over time. This represents the inverse of the anisotropic memory time tensor, used to control memory variables. The decay rate, This represents the driving force field after spatiotemporal convolution, used to characterize the comprehensive decomposed driving force formed by pressure driving, threshold response, and causal propagation within the historical spatial region and historical time range. This represents a spatiotemporally inseparable causal kernel function, used to describe the spatial distance traversed by a perturbation at the historical source point y. and time lag The subsequent impact on the current position x Representing historical moments Spatial location Entropy of pore structure The threshold response function of adjustment, Represents a unit tensor. Represents the driving force field With unit tensor The constructed tensor source terms are used to drive the second-order memory variables. The evolution, This represents the decomposition leading edge indicator function, used to control whether tensor memory decomposition rate calculation is enabled at the current position. The trace of a tensor is represented by the sum of the elements along the main diagonal of a second-order tensor. The trace of the second-order memory variable M is used to convert tensor memory states into scalar hydrate decomposition rates.

[0032] Optionally, the step of coupling the nonlocal memory hydrate decomposition rate model to the energy conservation equation and the two-phase Darcy flow pressure equation, and obtaining the decomposition result by iteratively solving using an explicit time-progression scheme, includes the following steps: Based on the current temperature and pressure fields, calculate the phase equilibrium distance and threshold function for each grid point; for the fractional Mitag-Leffler function kernel, use diffusion representation to approximate it as the sum of a finite number of exponential functions; solve the evolution equation of the anisotropic memory tensor and calculate the decomposition rate.

[0033] Secondly, to efficiently execute the hydrate decomposition method considering pressure wave time delay and pore structure entropy provided by this invention, this invention also provides a hydrate decomposition system considering pressure wave time delay and pore structure entropy, comprising: an input device, an output device, a processor, and a memory, wherein the input device, output device, processor, and memory are interconnected, and the memory stores program instructions for using the hydrate decomposition method considering pressure wave time delay and pore structure entropy. The hydrate decomposition system considering pressure wave time delay and pore structure entropy of this invention has a compact structure and stable performance, and can stably execute the hydrate decomposition method considering pressure wave time delay and pore structure entropy provided by this invention, further improving the overall applicability and practical application capability of this invention.

[0034] This invention addresses the inherent shortcomings of traditional decomposition kinetic models, such as locality, memorylessness, and linear assumptions. It quantifies the disorder of reservoir pore structure to obtain pore structure entropy and embeds it into kinetic parameters. A time-memory kernel dependent on saturation and structural entropy is constructed to characterize the historical memory effect of the decomposition process. A spatiotemporally inseparable causal kernel is proposed, incorporating pressure wave propagation delay to satisfy causality. A piecewise fractional-order response function with a permeability threshold is constructed to describe the nonlinear driving law of the decomposition rate. An anisotropic memory time tensor is introduced to reflect the directional stretching of the memory effect by fluid convection. Combined with a predictive-correction decomposition front indicator function, a nonlocal memory decomposition model is established, coupling the temperature and pressure field control equations to complete the time-progressive solution. This effectively compensates for the physical deficiencies of existing models, more realistically reflecting the influence of pore heterogeneity, pressure wave propagation, nonlinear permeability threshold, and anisotropic convection on hydrate decomposition, thus improving the physical realism and prediction accuracy of numerical simulations for depressurization mining. Attached Figure Description

[0035] Figure 1A flowchart of a hydrate decomposition method considering pressure wave time delay and pore structure entropy provided in an embodiment of the present invention; Figure 2 A framework diagram of a hydrate decomposition system considering pressure wave time delay and pore structure entropy is provided for an embodiment of the present invention. Detailed Implementation

[0036] Specific embodiments of the present invention will now be described in detail. It should be noted that the embodiments described herein are for illustrative purposes only and are not intended to limit the invention. In the following description, numerous specific details are set forth in order to provide a thorough understanding of the invention. However, it will be apparent to those skilled in the art that these specific details are not necessary to practice the invention. In other instances, well-known circuits, software, or methods have not been specifically described to avoid obscuring the invention.

[0037] Throughout this specification, references to "an embodiment," "an embodiment," "an example," or "an example" mean that a particular feature, structure, or characteristic described in connection with that embodiment or example is included in at least one embodiment of the invention. Therefore, the phrases "in an embodiment," "in an embodiment," "an example," or "an example" appearing in various places throughout the specification do not necessarily refer to the same embodiment or example. Furthermore, specific features, structures, or characteristics can be combined in one or more embodiments or examples in any suitable combination and / or sub-combination. Moreover, those skilled in the art will understand that the illustrations provided herein are for illustrative purposes and are not necessarily drawn to scale.

[0038] Please see Figure 1 This invention provides a hydrate decomposition method considering pressure wave time delay and pore structure entropy, comprising the following steps: S1. Calculate the pore structure entropy using the pore size distribution and coordination number distribution of the reservoir core, and use it as an intrinsic property of each numerical grid cell.

[0039] In the embodiments, the pore size distribution of reservoir cores from the simulated area is obtained by mercury intrusion porosimetry or X-ray CT scanning. and coordination number distribution .

[0040] Furthermore, we define the pore structure entropy. :

[0041] The larger the pore size, the more disordered the pore structure (wider pore size distribution and more complex connectivity). As an intrinsic property of each numerical grid point (or each representative cell), it is a constant in the simulation (if the reservoir is heterogeneous, it can be established). Field, extended from discrete core data to the entire reservoir through Kriging interpolation).

[0042] S2. Construct a time memory kernel that depends on saturation and structural entropy, and combine it with the decomposition rate threshold and pressure drop threshold to form a decomposition leading edge indicator function with a prediction-correction mechanism, which is used to control the enabled region of memory computation.

[0043] In the embodiment, the Mittag-Leffler time memory kernel function, which is dependent on saturation and structural leak, satisfies:

[0044]

[0045]

[0046] in, This represents a time-memory kernel function, used to characterize the hysteretic effect of pressure disturbances, decomposition states, or mass transfer processes at historical moments on the current hydrate decomposition rate. Indicates the current calculation time. This indicates the historical integration moment or the historical moment of action. Representing historical moments With the current moment The time interval between these intervals, i.e., the memory lag time. Indicates local hydrate saturation. Represents the entropy of pore structure. This represents the Mitag-Leffler function, used to describe the memory effect with fractional decay characteristics. Indicates local hydrate saturation and pore structure entropy The relevant fractional memory decay index, This represents the minimum value of the fractional memory decay exponent. This represents the maximum value of the fractional memory decay exponent. This represents the coefficient that indicates the influence of pore structure entropy on the fractional-order memory decay exponent, used to adjust the effect of pore structure disorder on memory decay characteristics. This represents the characteristic memory time related to local hydrate saturation Sh and pore structure entropy H. This represents the memory time of basic features, used to characterize the memory time scale under baseline conditions. This represents the moderating coefficient of local hydrate saturation on feature memory time. This represents the adjustment coefficient of pore structure entropy on feature memory time, used to characterize the effect of pore structure disorder on memory duration.

[0047] In this embodiment, the value range is as follows (example, which can be calibrated experimentally): , , , , , .

[0048] When structural entropy When it increases, Decrease (memory is more inclined towards long-term power-law decay). The increase (longer memory time) reflects a more severe retention of air bubbles in disordered pores.

[0049] Furthermore, define the decomposition leading edge indicator function. The memory model is enabled only in the active decomposition region.

[0050] Traditional methods, based on the current decomposition rate and pressure drop threshold, suffer from lag. This invention introduces a prediction-correction mechanism, including: Calculate the decomposition front position As isosurface, frontal normal velocity .

[0051] Predict the position of the leading edge in the next moment: .

[0052] Centered on the prediction frontier, distance Force all grid points within (Even if the current decomposition rate and pressure drop have not yet reached the threshold).

[0053] Correction step: If the deviation between the actual frontier and the predicted frontier is greater than... Then adjust in the next time step. Deviation. The final decomposition leading edge indicator function satisfies:

[0054] in, This represents the decomposition leading edge indicator function, used to determine spatial position. At the present moment Is it in an active decomposition region that requires the use of a non-local memory decomposition model? This indicates the spatial location or grid cell location within the reservoir's numerical computation domain. Indicates the current calculation time. This represents the rate of change of local hydrate saturation over time, used to characterize the activity level of hydrate decomposition processes within that grid cell. This represents the decomposition rate threshold or saturation change rate threshold. When the local hydrate saturation change rate exceeds this threshold, the region is considered to have entered an active decomposition state. This represents the local pressure drop, typically expressed as the difference between the phase equilibrium pressure and the current pressure, and is used to characterize the intensity of the pressure drop drive. This represents the pressure drop threshold, which is the minimum pressure drop required to trigger significant hydrate decomposition or activate the memory model. This represents the neighborhood radius, used to include grid cells near the decomposition leading edge but not yet reaching the threshold into the memory computation region in advance. Indicates the current or predicted position of the hydrate decomposition front. Indicates the position of the decomposed leading edge. Centered on The spatial neighborhood range of the neighborhood radius; when any condition is satisfied... 1 indicates that the non-local memory decomposition model is enabled at this location; when none of the above conditions are met, 0 indicates that the non-local memory decomposition model is not enabled at this location. In the example, , (These thresholds can be adjusted through numerical experiments and are not fixed limitations.)

[0055] S3. Perform spatiotemporal convolution operation on the time memory kernel, the spatiotemporally inseparable causal kernel and the threshold response function, and establish an integral form nonlocal memory hydrate decomposition rate model based on the decomposition leading edge indicator function.

[0056] In another embodiment, the traditional nonlocal model uses a separable form. Ignoring the finite speed of pressure wave propagation, this invention proposes a spacetime indivisible causal kernel that satisfies:

[0057] in, Represents a spacetime indivisible causal kernel, used to describe historical moments. Source Pressure disturbances or decomposition at a given point drive the current moment ,Location Nonlocal effects on the hydrate decomposition process, This indicates the current spatial location or target grid location to be calculated. This indicates the location of the historical disturbance source or the location of the integral source point. Indicates the current calculation time. Indicates the historical integration moment. This represents the time lag in the propagation of historical source disturbances to the current moment. Indicates the target location relative to the source point location Spatial distance between them This represents the time resolution or time smoothing parameter, used to approximate a finite-width response near the arrival time of the pressure wave. Indicates pressure wave velocity. It represents the effective bulk modulus of porous media, used to characterize the equivalent compressive stiffness of reservoir framework, pore fluid, and hydrate mixture systems. This represents the equivalent mixed density of gas, water, hydrates, and sedimentary framework in a porous medium. Indicates the pressure diffusion coefficient. Indicates the reference space attenuation length or the reference nonlocal action length. The pressure diffusion coefficient is used to characterize the ability of pressure disturbances to diffuse in porous media. Indicates reservoir permeability, Indicates the dynamic viscosity of a fluid. Indicates reservoir porosity. This represents the combined compressibility or overall compressibility, including the equivalent compressibility of the pore fluid and the porous media framework. This represents the reference pressure diffusion coefficient, used to normalize the local pressure diffusion coefficient.

[0058] This nucleus possesses causality: only It only makes a significant contribution after a time lag, when When the Gaussian function approaches the The nucleus degenerates into a separable form.

[0059] Furthermore, a dimensionless phase equilibrium distance is defined based on the fractional-order threshold response function of the phase equilibrium distance and structural entropy, satisfying:

[0060] Considering osmosis theory, the decomposition rate only... Exceeding the critical threshold Afterwards, it grows significantly, and the growth follows a power-law (fractional order). Simultaneously, the threshold value is related to the structural entropy: disordered pores ( The critical threshold of (larger) is lower, so construct a threshold response function that satisfies:

[0061]

[0062] in, This represents the threshold response function, used to describe the nonlinear response strength of the hydrate decomposition rate driven by the phase equilibrium pressure drop. It represents the dimensionless phase equilibrium distance or dimensionless pressure driving force, reflecting the degree to which the current pressure deviates from the hydrate phase equilibrium pressure. Represents the entropy of pore structure. This represents the critical initiation threshold related to pore structure entropy, when... If the threshold is less than or equal to this threshold, hydrate decomposition is considered insignificant or not effectively triggered. This represents the baseline critical start-up threshold, i.e., the dimensionless critical pressure driving force under baseline pore structure conditions. This represents the adjustment coefficient of pore structure entropy on the critical initiation threshold, used to characterize the influence of pore structure disorder on decomposition initiation conditions. Represents the normalization constant, such that , This indicates the inflection point of the threshold response function, when... Less than or equal to When the decomposition response increases with increasing pressure driving force, it exhibits a power-law growth; when Greater than At that time, due to factors such as mass transfer limitations, bubble blockage, or localized cooling, the response function enters the decay phase. This represents the fractional power-law exponent related to the pore structure entropy, used to describe the degree of nonlinearity in the growth of the decomposition response after exceeding a critical threshold. Indicates the baseline power law exponent. This indicates the degree to which the entropy of the pore structure modulates the power-law exponent. This represents the maximum reference value for pore structure entropy, used to normalize the pore structure entropy H. This represents the attenuation coefficient, used to control when... Greater than The rate at which the back threshold response function decays as the driving pressure continues to increase. Indicates the current temperature. This represents the phase equilibrium pressure corresponding to temperature T. This indicates the current pressure value.

[0063] This represents the phase equilibrium pressure corresponding to temperature T. Indicates the current pressure value. Fractional exponent. The rate of decomposition increases with increasing structural entropy, meaning that once the threshold is exceeded in disordered pores, the decomposition rate increases faster (a steeper power law).

[0064] Based on this, a decomposition rate model for nonlocal memory hydrates is established, wherein the decomposition rate satisfies:

[0065] in, Indicates local hydrate saturation. Represents the entropy of pore structure. This indicates the current spatial location or target grid location to be calculated. Indicates the current calculation time. Indicates spatial location At the present moment The rate of change in hydrate saturation at a given location is used to characterize the rate of hydrate decomposition at that location. This represents the decomposition leading edge indicator function, used to control whether the nonlocal memory decomposition model is enabled at this location. This represents the spatial computational domain or nonlocal integration region of the hydrate reservoir. This represents the spatial integral variable, i.e., the location of the historical source point of the nonlocal action. This represents the time-integral variable, i.e., the historical moments of action. This represents the time memory kernel function, used to describe the memory effect of historical decomposition on the current decomposition rate. Representing historical moments Spatial location Local hydrate saturation at the location, Indicates spatial location The entropy of the pore structure at that location, Represents a spacetime inseparable causal kernel function, used to describe the source point. Historical disturbances at a location, after propagation by pressure waves, have a time lag in affecting the location. The impact of the location Representing historical moments Spatial location The dimensionless phase equilibrium distance or pressure driving force at the location. Representing historical moments Spatial location The threshold response function modulated by the entropy of the pore structure. This indicates a joint integration over historical time and spatial source points.

[0066] S4. Calculate the Peclai number using the grid Darcy velocity, extend the scalar characteristic memory time to a second-order symmetric anisotropic memory time tensor, construct a second-order tensor type memory variable and establish an evolution equation, decompose the rate to take the trace of the memory tensor, and use it to characterize the directional stretching effect of fluid convection on the memory effect.

[0067] First, define the grid Peckle number. ,in For Darcy speed, Let be the molecular diffusion coefficient, and the memory time tensor be:

[0068]

[0069]

[0070] in, Indicates local hydrate saturation. Represents the entropy of pore structure. This represents the second-order anisotropic memory time tensor obtained by scalar feature memory time extension. Indicates the local hydrate saturation and pore structure entropy Determined scalar basic feature memory time, Represents the grid Peckley number, Indicates the reference Peckley number, used for grid Peckley numbers. Normalization was performed, and the extent to which convection enhanced the anisotropy of the memory time tensor was controlled. This represents the grid Darcy velocity vector or the apparent velocity vector of the pore fluid. This represents the square of the magnitude of the velocity vector v. Represents velocity vector Its tensor product with itself is used to construct a directional tensor that enhances the flow direction. This represents the unit direction tensor along the fluid flow direction, used to characterize the directional stretching of the memory effect in the mainstream direction. This represents a second-order symmetric tensor memory variable used to record anisotropic memory states formed by the combined effects of historical pressure perturbations, decomposition drives, and fluid convection. This represents the rate of change of the second-order tensor memory variable over time. This represents the inverse of the anisotropic memory time tensor, used to control memory variables. The decay rate, This represents the driving force field after spatiotemporal convolution, used to characterize the comprehensive decomposed driving force formed by pressure driving, threshold response, and causal propagation within the historical spatial region and historical time range. This represents a spatiotemporally inseparable causal kernel function, used to describe the spatial distance traversed by a perturbation at the historical source point y. and time lag The subsequent impact on the current position x Representing historical moments Spatial location Entropy of pore structure The threshold response function of adjustment, Represents a unit tensor. Represents the driving force field With unit tensor The constructed tensor source terms are used to drive the second-order memory variables. The evolution, This represents the decomposition leading edge indicator function, used to control whether tensor memory decomposition rate calculation is enabled at the current position. The trace of a tensor is represented by the sum of the elements along the main diagonal of a second-order tensor. The trace of the second-order memory variable M is used to convert tensor memory states into scalar hydrate decomposition rates.

[0071] set up And set an upper limit. Prevent numerical overflow.

[0072] Introducing second-order symmetric tensor memory variables (6 independent components), its evolution equation is:

[0073] in: The driving force field after spatiotemporal convolution. It is a unit tensor.

[0074] Finally, the trace of the tensor is taken as the decomposition rate:

[0075] S5. Couple the nonlocal memory hydrate decomposition rate model to the energy conservation equation and the two-phase Darcy flow pressure equation, and use an explicit time-progression scheme to iteratively solve for the decomposition results.

[0076] Substituting the above decomposition rate into a classical multi-field coupled system The energy equation then satisfies: ; The pressure equation (two-phase Darcy) satisfies: ; Based on this, explicit time advancement is adopted, and execution is performed sequentially within each time step: 1. Calculate the phase equilibrium distance at each grid point based on the current temperature and pressure field. and threshold function .

[0077] 2. For fractional-order Mittag-Leffler kernels ( This paper uses diffusion representation (a known mathematical transformation) to approximate the integral memory as the sum of a finite number of exponential functions, thereby transforming the integral memory into a set of conventional differential equations and avoiding the need to store all historical data. The specific coefficients of this transformation can be obtained through offline numerical optimization, independent of experimental data.

[0078] 3. Solve for the anisotropic memory tensor The evolution equation:

[0079] Discretize using the first-order explicit Euler scheme: .

[0080] 4. Calculate the decomposition rate .

[0081] 5. Substitute the energy equation and pressure equation, and update the temperature and pressure fields using the conventional finite volume method.

[0082] 6. Update saturation .

[0083] 7. Proceed to the next time step In a specific embodiment, taking a one-dimensional simplified problem of a hydrate reservoir as an example, the implementation steps of this scheme are explained (all parameters below are for illustrative purposes only and need to be calibrated according to reservoir characteristics in actual applications): Grid generation: Discretizing the reservoir into equidistant grids, grid spacing .

[0084] Pore ​​structure draft: The pore structure of this area was obtained through core analysis. (Assuming the data is known, the actual calculation needs to be based on mercury intrusion porosimetry or CT data).

[0085] Model parameter settings (example values, which can be adjusted through experimental calibration):

[0086]

[0087] Initial conditions: given temperature field Pressure field saturation field And physical properties such as permeability and porosity.

[0088] Time step: Select (Or adjust according to CFL conditions).

[0089] Then, the calculation process is as follows: 1. At the beginning of each time step, predict the leading edge at the current time step based on the leading edge position of the previous time step, and update the decomposed leading edge indicator function. .

[0090] 2. Calculate the value of each grid point. and .

[0091] 3. The fractional-order memory kernel is approximated as an exponential sum (coefficients are calculated offline) using diffusion representation, and then the spatial convolution is solved. (It can be approximated by summing over a finite region).

[0092] 4. Update the tensor : .

[0093] 5. Calculate the decomposition rate .

[0094] 6. Solve the energy equation and pressure equation, and update them. , , .

[0095] 7. Adjust the memory time tensor according to the frontier velocity. (If leading edge speed adjustment is enabled).

[0096] 8. Proceed to the next time step.

[0097] Finally, the output records the decomposed rate field, latent heat flux field, and... for each time step. The distribution is then analyzed to obtain a hotspot evolution map.

[0098] It should be noted that this embodiment does not provide specific numerical results (such as "gas production increased by X%)", because these results depend on specific reservoir parameters and boundary conditions, and require actual simulation operation to obtain. Any unverified figures are fictitious. Researchers or engineers using this method should run simulations in their own computing environment and compare them with traditional models to verify the effectiveness of this method.

[0099] Parameter calibration method (not experimental data, only illustrating the process) All model parameters ( (etc.) can all be calibrated through the following process: 1. Decomposition experiments were conducted on multiple sets of core samples with different pore structures at different depressurization rates, and the gas production rate curves were recorded.

[0100] 2. Simultaneously, the core samples from each group were calculated using CT images. value.

[0101] 3. Use the model of this invention for inversion fitting (e.g., using particle swarm optimization algorithm) to find the parameter set that minimizes the error between the simulated curve and the experimental curve.

[0102] 4. Use the calibrated parameters for full-scale simulation of the target reservoir.

[0103] It should be noted that the specific implementation methods described above, such as image processing, numerical simulation, and the construction and training of machine learning models, can all be accomplished by the processor by calling the corresponding computer program instructions stored in memory. Those skilled in the art can implement the above functions using algorithms and tools known in the prior art, according to actual needs.

[0104] Please see Figure 2In an embodiment, to efficiently execute the hydrate decomposition method considering pressure wave time delay and pore structure entropy provided by the present invention, the present invention also provides a hydrate decomposition system considering pressure wave time delay and pore structure entropy, comprising: an input device 1, an output device 2, a processor 3, and a memory 4, wherein the input device 1, output device 2, processor 3, and memory 4 are interconnected, and the memory 4 stores program instructions for executing the steps of the hydrate decomposition method considering pressure wave time delay and pore structure entropy. The hydrate decomposition system considering pressure wave time delay and pore structure entropy of the present invention has a compact structure and stable performance, and can stably execute the hydrate decomposition method considering pressure wave time delay and pore structure entropy of the present invention, further improving the overall applicability and practical application capability of the present invention.

[0105] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be covered within the scope of the present invention.

Claims

1. A method for hydrate decomposition considering pressure wave time delay and pore structure entropy, characterized in that, Includes the following steps: The pore structure entropy is calculated using the pore size distribution and coordination number distribution of reservoir cores and used as an intrinsic property of each numerical grid cell. A time-memory kernel that depends on saturation and structural entropy is constructed. Combined with the decomposition rate threshold and pressure drop threshold, a decomposition leading edge indicator function with a prediction-correction mechanism is formed to control the enabled region of memory computation. The time memory kernel, the spatiotemporally inseparable causal kernel, and the threshold response function are subjected to spatiotemporal convolution operation. Based on the decomposition leading edge indicator function, an integral form of the nonlocal memory hydrate decomposition rate model is established. The Peckley number is calculated by grid Darcy velocity, and the scalar characteristic memory time is extended to a second-order symmetric anisotropic memory time tensor. A second-order tensor memory variable is constructed and an evolution equation is established. The decomposition rate is taken as the trace of the memory tensor to characterize the directional stretching effect of fluid convection on the memory effect. The nonlocal memory hydrate decomposition rate model is coupled to the energy conservation equation and the two-phase Darcy flow pressure equation, and the decomposition results are obtained by iterative solution using an explicit time-progression scheme. The calculation of pore structure entropy using the pore size distribution and coordination number distribution of reservoir cores satisfies: in, This represents the entropy of the pore structure; the larger the value, the more disordered the pore structure. This represents the maximum pore size in the reservoir core pore size distribution. This represents the minimum pore size in the reservoir core pore size distribution. Indicates aperture as The normalized aperture probability density function at time satisfies , This represents the coordination number of pore nodes in a pore network. Indicates the coordination number is The normalized probability distribution function satisfies 1; The constructed saturation and structural entropy-dependent time memory kernel satisfies: in, This represents a time-memory kernel function, used to characterize the hysteretic effect of pressure disturbances, decomposition states, or mass transfer processes at historical moments on the current hydrate decomposition rate. Indicates the current calculation time. This indicates the historical integration moment or the historical moment of action. Representing historical moments With the current moment The time interval between these intervals, i.e., the memory lag time. Indicates local hydrate saturation. Represents the entropy of pore structure. This represents the Mitag-Leffler function, used to describe the memory effect with fractional decay characteristics. Indicates local hydrate saturation and pore structure entropy The relevant fractional memory decay index, This represents the minimum value of the fractional memory decay exponent. This represents the maximum value of the fractional memory decay exponent. This represents the coefficient that indicates the influence of pore structure entropy on the fractional-order memory decay exponent, used to adjust the effect of pore structure disorder on memory decay characteristics. This represents the feature memory time related to local hydrate saturation Sh and pore structure entropy H. This represents the memory time of basic features, used to characterize the memory time scale under baseline conditions. This represents the moderating coefficient of local hydrate saturation on feature memory time. This represents the adjustment coefficient of pore structure entropy on feature memory time, used to characterize the effect of pore structure disorder on memory duration.

2. The hydrate decomposition method considering pressure wave time delay and pore structure entropy according to claim 1, characterized in that, The decomposition rate threshold and pressure drop threshold are combined to form a decomposition leading edge indicator function with a prediction-correction mechanism, satisfying: in, This represents the decomposition leading edge indicator function, used to determine spatial position. At the present moment Is it in an active decomposition region that requires the use of a non-local memory decomposition model? This indicates the spatial location or grid cell location within the reservoir's numerical computation domain. Indicates the current calculation time. This represents the rate of change of local hydrate saturation over time, used to characterize the activity level of hydrate decomposition processes within that grid cell. This represents the decomposition rate threshold or the saturation change rate threshold. This represents the local pressure drop, which is the difference between the phase equilibrium pressure and the current pressure. It is used to characterize the intensity of the pressure drop drive. This represents the pressure drop threshold, which is the minimum pressure drop required to trigger significant hydrate decomposition or activate the memory model. This represents the neighborhood radius, used to include grid cells near the decomposition leading edge but not yet reaching the threshold into the memory computation region in advance. Indicates the current or predicted position of the hydrate decomposition front. Indicates the position of the decomposed leading edge. Centered on The spatial neighborhood range of the neighborhood radius. 1 indicates that the non-local memory decomposition model is enabled. 0 indicates that the nonlocal memory decomposition model is not enabled.

3. The hydrate decomposition method considering pressure wave time delay and pore structure entropy according to claim 1, characterized in that, The spacetime indivisible causal kernel satisfies: in, Represents a spacetime indivisible causal kernel, used to describe historical moments. Source Pressure disturbances or decomposition at a given point drive the current moment ,Location Nonlocal effects on the hydrate decomposition process, This indicates the current spatial location or target grid location to be calculated. This indicates the location of the historical disturbance source or the location of the integral source point. Indicates the current calculation time. Indicates the historical integration moment. This represents the time lag in the propagation of historical source disturbances to the current moment. Indicates the target location relative to the source point location Spatial distance between them This represents the time resolution or time smoothing parameter, used to approximate a finite-width response near the arrival time of the pressure wave. Indicates pressure wave velocity. It represents the effective bulk modulus of porous media, used to characterize the equivalent compressive stiffness of reservoir framework, pore fluid, and hydrate mixture systems. This represents the equivalent mixed density of gas, water, hydrates, and sedimentary framework in a porous medium. Indicates the pressure diffusion coefficient. Indicates the reference space attenuation length or the reference nonlocal action length. The pressure diffusion coefficient is used to characterize the ability of pressure disturbances to diffuse in porous media. Indicates reservoir permeability, Indicates the dynamic viscosity of a fluid. Indicates reservoir porosity. This represents the combined compressibility or overall compressibility, including the equivalent compressibility of the pore fluid and the porous media framework. This represents the reference pressure diffusion coefficient, used to normalize the local pressure diffusion coefficient.

4. The hydrate decomposition method considering pressure wave time delay and pore structure entropy according to claim 1, characterized in that, The threshold response function satisfies: in, This represents the threshold response function, used to describe the nonlinear response strength of the hydrate decomposition rate driven by the phase equilibrium pressure drop. It represents the dimensionless phase equilibrium distance or dimensionless pressure driving force, reflecting the degree to which the current pressure deviates from the hydrate phase equilibrium pressure. Represents the entropy of pore structure. This represents the critical initiation threshold related to pore structure entropy. This represents the baseline critical start-up threshold, i.e., the dimensionless critical pressure driving force under baseline pore structure conditions. This represents the adjustment coefficient of pore structure entropy on the critical initiation threshold, used to characterize the influence of pore structure disorder on decomposition initiation conditions. Represents the normalization constant, such that , This indicates the inflection point of the threshold response function. This represents the fractional power-law exponent related to the pore structure entropy, used to describe the degree of nonlinearity in the growth of the decomposition response after exceeding a critical threshold. Indicates the baseline power law exponent. This indicates the degree to which the entropy of the pore structure modulates the power-law exponent. This represents the maximum reference value for pore structure entropy, used to normalize the pore structure entropy H. Indicates the attenuation coefficient. Indicates the current temperature. This represents the phase equilibrium pressure corresponding to temperature T. This indicates the current pressure value.

5. The hydrate decomposition method considering pressure wave time delay and pore structure entropy according to claim 1, characterized in that, The nonlocal memory hydrate decomposition rate model satisfies: in, Indicates local hydrate saturation. Represents the entropy of pore structure. This indicates the current spatial location or target grid location to be calculated. Indicates the current calculation time. Indicates spatial location At the present moment The rate of change in hydrate saturation at a given location is used to characterize the rate of hydrate decomposition at that location. This represents the decomposition leading edge indicator function, used to control whether the nonlocal memory decomposition model is enabled at this location. This represents the spatial computational domain or nonlocal integration region of the hydrate reservoir. This represents the spatial integral variable, i.e., the location of the historical source point of the nonlocal action. This represents the time-integral variable, i.e., the historical moments of action. This represents the temporal memory kernel function, used to describe the memory effect of historical decomposition on the current decomposition rate. Representing historical moments Spatial location Local hydrate saturation at the location, Indicates spatial location The entropy of the pore structure at that location, Represents a spacetime inseparable causal kernel function, used to describe the source point. Historical disturbances at a location, after propagation by pressure waves, have a time lag in affecting the location. The impact of the location Representing historical moments Spatial location The dimensionless phase equilibrium distance or pressure driving force at the location. Representing historical moments Spatial location The threshold response function modulated by the entropy of the pore structure. This indicates a joint integration over historical time and spatial source points.

6. The hydrate decomposition method considering pressure wave time delay and pore structure entropy according to claim 1, characterized in that, The scalar feature memory time is extended to a second-order symmetric anisotropic memory time tensor, a second-order tensor type memory variable is constructed, and an evolution equation is established. The decomposition rate is taken from the trace of the memory tensor, satisfying: in, Indicates local hydrate saturation. Represents the entropy of pore structure. This represents the second-order anisotropic memory time tensor obtained by scalar feature memory time extension. Indicates the local hydrate saturation and pore structure entropy Determined scalar basic feature memory time, Represents the grid Peckley number, Indicates the reference Peckley number, used for grid Peckley numbers. Normalization was performed, and the extent to which convection enhanced the anisotropy of the memory time tensor was controlled. This represents the grid Darcy velocity vector or the apparent velocity vector of the pore fluid. This represents the square of the magnitude of the velocity vector v. Represents velocity vector Its tensor product with itself is used to construct a directional tensor that enhances the flow direction. This represents the unit direction tensor along the fluid flow direction, used to characterize the directional stretching of the memory effect in the mainstream direction. This represents a second-order symmetric tensor memory variable used to record anisotropic memory states formed by the combined effects of historical pressure perturbations, decomposition drives, and fluid convection. This represents the rate of change of the second-order tensor memory variable over time. This represents the inverse of the anisotropic memory time tensor, used to control memory variables. The decay rate, This represents the driving force field after spatiotemporal convolution, used to characterize the comprehensive decomposed driving force formed by pressure driving, threshold response, and causal propagation within the historical spatial region and historical time range. This represents a spatiotemporally inseparable causal kernel function, used to describe the spatial distance traversed by a perturbation at the historical source point y. and time lag The subsequent impact on the current position x Representing historical moments Spatial location Entropy of pore structure The threshold response function of adjustment, Represents a unit tensor. Represents the driving force field With unit tensor The constructed tensor source terms are used to drive the second-order memory variables. The evolution, This represents the decomposition leading edge indicator function, used to control whether tensor memory decomposition rate calculation is enabled at the current position. The trace of a tensor is represented by the sum of the elements along the main diagonal of a second-order tensor. The trace of the second-order memory variable M is used to convert tensor memory states into scalar hydrate decomposition rates.

7. The hydrate decomposition method considering pressure wave time delay and pore structure entropy according to claim 1, characterized in that, The process of coupling the nonlocal memory hydrate decomposition rate model to the energy conservation equation and the two-phase Darcy flow pressure equation, and obtaining the decomposition result by iteratively solving using an explicit time-progression scheme, includes the following steps: Calculate the phase equilibrium distance and threshold function for each grid point based on the current temperature and pressure field. For a fractional Mitag-Leffler function kernel, the diffusion representation approximates it as the sum of a finite number of exponential functions; Solve the evolution equation of the anisotropic memory tensor and calculate the decomposition rate.

8. A hydrate decomposition system considering pressure wave time delay and pore structure entropy, characterized in that, The hydrate decomposition system considering pressure wave time delay and pore structure entropy includes: an input device, an output device, a processor, and a memory, wherein the input device, output device, processor, and memory are interconnected, and the memory stores program instructions for executing the hydrate decomposition method considering pressure wave time delay and pore structure entropy as described in any one of claims 1-7.

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