CN-121997840-A - Method for determining optimal flow pressure and drainage and production time of gas well based on oil reservoir numerical simulation technology

CN121997840ACN 121997840 ACN121997840 ACN 121997840ACN-121997840-A

Abstract

The invention discloses a method for determining optimal flow pressure and drainage time of a gas well based on oil reservoir numerical simulation, which belongs to the technical field of oil and gas exploitation and is characterized by comprising the following steps of a, calculating a gas phase flow capacity index GFI representing gas phase flow efficiency of a near well in an oil reservoir numerical simulation process, b, calculating a ratio R (liquid carrying coefficient) of current actual gas yield to critical liquid carrying gas yield, c, analyzing the absolute magnitude of the change trend of the GFI and the R value, and d, outputting a decision instruction for flow pressure control or artificial lifting intervention of the gas well based on a collaborative analysis result of the GFI trend and the R value. According to the invention, the gas phase flow efficiency of the near-wellbore zone is quantified by defining the gas phase flow capacity index (GFI), and a double-signal collaborative decision mechanism is constructed by combining the wellbore fluid carrying coefficient (R), so that the prospective judgment of the flow pressure optimization and the drainage and production time is realized.

Inventors

NI FENG
MA RUI
SUN BO
LIU KUN
FENG MINGMING
WANG HU
LIU QINGSHAN

Assignees

天津枫火石油科技有限公司

Dates

Publication Date: 20260508
Application Date: 20260307

Claims (9)

1. The method for determining the optimal flow pressure and the drainage and production time of the gas well based on the oil reservoir numerical simulation is characterized by comprising the following steps of: a. Extracting well grid parameters, production dynamic data and fluid PVT properties of a gas well in a time step after each nonlinear iteration of the reservoir numerical simulation converges; b. According to the extracted parameters, calculating a gas phase flow capacity index GFI representing the gas phase flow efficiency of the near well, and simultaneously calculating a critical liquid carrying flow q crit and a ratio of actual gas yield to the critical liquid carrying flow, namely a liquid carrying coefficient R; c. Analyzing the dynamic variation trend of the GFI, identifying the peak point of the GFI, determining the optimal flow pressure P opt of the gas well corresponding to the peak point, and calculating the accumulated relative decreasing delta of the GFI after the GFI is subjected to self-peak; d. based on the change trend of GFI, the relative relation between accumulated relative amplitude reduction delta and liquid carrying coefficient R, outputting a decision instruction of gas well flow pressure control or manual lifting drainage intervention through a dual-signal collaborative decision matrix; e. according to the decision instruction, automatically adjusting the production constraint condition of the gas well in the subsequent numerical simulation time step, or triggering an artificial lifting model to form closed-loop control.
2. The method of claim 1, wherein the gas phase flow capacity index GFI in step ② is calculated as: Wherein k is the absolute permeability of the well grid, mum 2, k rg is the gas phase relative permeability of the well grid, no dimension, and mu g is the gas viscosity under the well bottom condition, mPa.s; the pressure gradient is the pressure gradient amplitude at the well lattice, MPa/m, ρ g , ρ w is the density of gas and liquid under the well bottom condition, kg/m3, WOR is the water-gas ratio, the dimensionless is the empirical index (usually taking 0.5-1.0), and the dimensionless is the alpha.
3. The method of claim 2, wherein k rg is obtained from a look-up table of the water saturation of the current well grid S w , wherein μ g 、ρ g 、ρ w is obtained from a PVT model calculated from the current bottom hole pressure P wf and temperature T, wherein the WOR is obtained from a calculation of the actual gas production q g and water production q w of the gas well, and wherein α is determined by fitting historical production data of the gas field.
4. The method of claim 1, wherein the identifying the peak point of GFI in step ③ is performed by comparing the GFI value GFI (t) at the current time step with all GFI values in the history sequence, and if GFI (t) is the history maximum value, marking the current time step as the GFI peak time, the bottom hole flow pressure corresponding to the time step as the optimal flow pressure P opt , and the calculation formula of the accumulated relative decrease delta of GFI from peak value is: Delta= (GFI max −GFI(t))/GFI max , where GFI max is the peak GFI.
5. The method of claim 1, wherein the core logic of the dual signal collaborative decision matrix in step 4) is: a. outputting a command for continuously optimizing and reducing the bottom hole flow pressure when the GFI is in an ascending trend and R is more than 1.2; b. Outputting drainage early warning and preparing artificial lifting instructions when the GFI is firstly reduced from a peak value, the relative reduction delta is 5% -15% and R is more than 1.0; c. When the GFI is continuously lowered and R is rapidly approaching 1.0, outputting an instruction for immediately activating artificial lifting and implementing drainage; d. When GFI is severely reduced and R is less than 0.8, outputting an instruction for taking emergency strong drainage measures; e. Otherwise, outputting instructions for maintaining the current production system and continuously monitoring.
6. The method of claim 1, wherein the critical carrier flow rate q crit in step ② is calculated by an integrated Turner model or a Li Min model, and the carrier flow rate R is calculated by the formula r=q actual /q crit , where q actual is the actual gas production of the gas well.
7. The method of claim 1, wherein adjusting production constraints of the gas well in step ⑤ comprises changing the constant production to constant production and modifying the bottom hole flow target value, wherein the artificial lift model comprises a gas lift model and a pumping model, and wherein the preset lift process parameters are loaded after triggering.
8. A non-transitory computer readable storage medium storing a computer program, wherein the computer program when executed by a processor implements the method of determining optimal flow pressure and timing for gas well drainage based on reservoir numerical simulation of any one of claims 1-7.
9. The intelligent decision system for gas well drainage based on oil reservoir numerical simulation is characterized by comprising a processor and a memory, wherein the memory stores a computer program, the method of any one of claims 1-7 is realized when the processor executes the computer program, the system is integrated in an oil reservoir numerical simulator, the system comprises a data acquisition module, a GFI calculation engine, a critical liquid carrying analyzer, an intelligent decision engine and a control instruction executor, and the modules cooperatively complete gas well optimal flow pressure determination and drainage time judgment and output decision instructions to the numerical simulator or an on-site production control system.

Description

Method for determining optimal flow pressure and drainage and production time of gas well based on oil reservoir numerical simulation technology Technical Field The invention belongs to the technical field of intelligent development of oil and gas fields and numerical reservoir simulation, and particularly relates to a high-water-content gas reservoir flow pressure collaborative optimization and intelligent decision-making method integrating near-well gas phase flow efficiency diagnosis and a shaft liquid carrying critical criterion. Background In the middle and later stages of high water-content gas reservoir development, gas well production management faces the core contradiction of 'depressurization and yield increase' and 'control flooding', the existing gas well flow pressure optimization and drainage and production timing judgment technology has obvious defects, the obvious defects are mainly represented by double fracture of oil reservoir side analysis and shaft side criteria, and a decision mechanism lacks foresight and synergetic. The traditional oil reservoir numerical simulation technology only focuses on the prediction of macroscopic yield and pressure, does not establish quantitative diagnosis indexes for the gas phase flow efficiency of near well zones, and particularly cannot accurately represent the effect of gas phase relative permeability change on near well flow under the influence of water invasion, so that the trend of formation flow efficiency deterioration cannot be recognized in advance. Critical fluid carrying flow (q crit) is calculated by depending on a Turner or Li Min model on the side of the well bore, the method can only guide the gas well to produce under the condition of not lower than q crit, and the occurrence of dropsy can be judged only when the actual yield (q actual) is lower than q crit, and the method belongs to post judgment and the optimal opportunity of preventive drainage intervention is lost. Overall, the core defect of the prior art is that oil reservoir simulation is disjointed with shaft analysis, early warning signals are delayed, decision bases depend on single and fixed-threshold indexes, oil reservoir-shaft coupling relation which dynamically changes in the development process cannot be responded, and accurate optimization of gas well flow pressure and prospective judgment of drainage and production time are difficult to achieve. Disclosure of Invention The invention aims to overcome the defects of the prior art, provides a method capable of realizing oil reservoir-shaft integrated diagnosis in oil reservoir numerical simulation and providing prospective and synergistic decision signals so as to solve the problem of gas well management in the middle and later stages of high-water-content gas reservoir development. The invention is realized by the following technical scheme: the method for determining the optimal flow pressure and the drainage and production time of the gas well based on the oil reservoir numerical simulation is characterized by comprising the following steps of: a. defining a gas phase flow capacity index (Gas Flowability Index, GFI) that comprehensively reflects the degree of near-well gas phase flow control; b. Establishing a dual-signal collaborative decision mechanism based on the relative relation between GFI dynamic trend and liquid carrying coefficient (q actual/qcrit); c. An intelligent algorithm which runs automatically in a numerical simulator and is used for optimizing the flow pressure and judging the drainage intervention time is established based on a double-signal collaborative decision mechanism. Said step a is specifically by creating a gas phase flow capacity index (GFI). GFI aims to more comprehensively quantify the throughput of an effective gas phase fluid in near wellbore, and its calculation formula is shown in formula 1: Wherein k is absolute permeability of the well pattern, mu m2, and represents basic diversion capacity of the reservoir, k rg is gas phase relative permeability of the well pattern, dimensionless, obtained by looking up a table of current water saturation (S w), the parameter is a core variable reflecting negative effects of water invasion, the value of the parameter is rapidly reduced along with the rise of (S w), mu g is gas viscosity under the bottom hole condition, mPa.s, the gas viscosity is obviously changed along with temperature and pressure, and the flow resistance of the gas is directly influenced, and the parameter is calculated according to the current bottom hole pressure P wf and the temperature T through a PVT model; The method is characterized in that the driving energy provided by the current production pressure difference is reflected in MPa/m for the pressure gradient amplitude value at a well grid, the driving energy provided by the current production pressure difference is a direct representation for reducing the positive effect of the flow pressure, rho g, ρw is the density o