Oil reservoir simulation auxiliary history fitting method and system, storage medium and equipment

Abstract

The invention relates to an oil reservoir simulation auxiliary history fitting method and system, a storage medium and equipment, and the method comprises the steps: tracking the flight time of a pressure wave passing through each grid in a preset oil reservoir model from a well point, and defining a single well sensitive area of each well in a three-dimensional space according to the flight time;And constructing a historical fitting objective function, carrying out optimization solution on the historical fitting objective function by using a model parameter average value of a preset oil reservoir model in the single well sensitive area, and taking a value of an independent variable corresponding to a minimum value of the historical fitting objective function as an optimal estimation output of model parameters in oil reservoir simulation auxiliary historical fitting. According to the method, the flight time of pressure waves passing through each grid in a preset oil reservoir model from a well point is tracked; the single well sensitive area of each well in the three-dimensional space is defined according to the flight time, the average value of the model parameters in the singlewell sensitive area serves as the parameter variable in the historical fitting objective function, the dimension of the variable is greatly reduced, and the calculation efficiency is improved.

Description

technical field [0001] The present invention relates to the technical field of reservoir exploitation, in particular to a reservoir simulation-assisted history matching method, system, storage medium and equipment. Background technique [0002] Reservoir numerical simulation history matching is a key link in reservoir numerical simulation, and it is the guarantee to correctly predict the future development performance of the reservoir and formulate the optimal production and development plan of the oilfield. History matching is a typical reservoir inverse problem. By repeatedly adjusting reservoir model parameters, the calculation results of the model are consistent or close to the historical dynamic production data. Traditional artificial history matching is slow and accurate, and relies on reservoir workers' analysis and understanding of reservoirs and fitting experience, which is blind and arbitrary, and cannot meet the requirements of high-efficiency and real-time oilfie...

AI Technical Summary

Problems solved by technology

In assisted history matching research, researchers usually obtain single-well sensitive areas based on prior geological information (such as sedimentary facies) combined with distance truncation method, but the distance truncation is artificial and not accurate enough.

In addition, the reservoir model parameters that need to be inverted for history matching are usually in the hundreds of thousands. They are directly calculated using mainstream non-gradient optimization algorithms such as simulated annealing algorithm, genetic algorithm, random perturbation approximate gradient algorithm, and ensemble Kalman filter. Big

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