Reservoir simulation fast matching method based on dimension reduction strategy

A technology of reservoir simulation and reservoir model, which is applied in the field of fast fitting of reservoir simulation based on dimensionality reduction strategy, which can solve the problems of unbearable calculation cost, slow convergence speed, and high time consumption.

Active Publication Date: 2016-07-27
CHINA PETROLEUM & CHEM CORP +1
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Problems solved by technology

In recent years, research on this type of method has received more attention, such as genetic algorithm, particle swarm optimization algorithm, random perturbation approximation algorithm SPSA, etc., but the convergence speed of this type of method is slow, and it often requires thousands of It takes tens of thousands of calculations to converge. Since the reservoir numerical simulation operation itself is time-consuming, the calculation cost of applying this type of method for reservoir simulation history fitting is unbearable

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  • Reservoir simulation fast matching method based on dimension reduction strategy
  • Reservoir simulation fast matching method based on dimension reduction strategy
  • Reservoir simulation fast matching method based on dimension reduction strategy

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Embodiment

[0110] The Brugge reservoir model contains 9 sublayers, the plane grid system is divided into 139×48, and the total number of effective grids is 44,550. The parameters that need to be inverted in the history matching include the net-to-gross ratio of each grid, the permeability rate, porosity and initial oil saturation, a total of 267,000. Figure 2a-Figure 2d The dobs in the figure are observation data, PriorMean is an unfitting model to calculate the bottomhole flow pressure curve, and MAP is an unfitted bottomhole flow pressure curve, so it shows that the fitting efficiency of this method is very high, and it is fully fitted. Figure 2a-Figure 2d Fitting curves for different well bottomhole flowing pressures.

[0111] In the history matching, the ECLIPSE commercial simulator is selected to carry out the reservoir simulation calculation. Using the method proposed by the present invention, after 211 calculations, the final dynamic data fitting results of some oil wells are ob...

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Abstract

The present invention is a fast fitting method for reservoir simulation based on a dimensionality reduction strategy; the specific steps of the method are: Step 1, input data: input prior reservoir model m pr , Model covariance matrix C M , real observed dynamic data d obs , Observation data covariance matrix C D ; Step 2, establish the objective function O(m) to be optimized: use the prior reservoir model m pr and the model covariance matrix C M Combining with the historical fitting method, establish the objective function O(m) to be optimized; step 3, carry out dimension reduction processing on the objective function O(m) to be optimized, and obtain the historical fitting objective function O(p); step 4, use the The history fitting objective function O(p) obtains the model parameter m of the real reservoir.

Description

technical field [0001] The invention relates to a reservoir numerical simulation method, in particular to a fast fitting method for reservoir simulation based on a dimension reduction strategy. Background technique [0002] Reservoir simulation history matching is an extremely important work in oil and gas field development research. It mainly uses numerical simulation technology to invert and correct reservoir parameters by fitting the actual production performance data of oil and water wells, so that the numericalized reservoir The model conforms to the actual development state of the reservoir, and provides a basis for the design and formulation of the later oilfield development plan. [0003] At present, engineers generally use the method of manual trial calculation for history fitting. In the process of history matching, since geological parameters such as interwell porosity, permeability, faults, and fractures are mainly obtained indirectly through well point measurem...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F9/455
Inventor 康志江张允崔书岳邱立伟李红凯赵辉
Owner CHINA PETROLEUM & CHEM CORP
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