Input parameter analysis method and device of multilayer interwell dynamic connectivity model

Abstract

The invention provides an input parameter analysis method of a multilayer interwell dynamic connectivity model. The input parameter analysis method comprises the steps that distribution modes of production wells and water injection wells in a current block are determined, and interwell dynamic connectivity coefficients between the water injection wells and the production wells in the current block, and multilayer dissymmetry coefficients corresponding to the interwell dynamic connectivity coefficients are obtained through calculation based on the multilayer interwell dynamic connectivity model; overdetermined coefficients corresponding to the multilayer interwell dynamic connectivity model are determined based on production conditions and production data of the production wells in the block; and optimal overdetermined coefficients are selected based on the multilayer dissymmetry coefficients and the overdetermined coefficients so as to determine the number of data points in input parameters of the multilayer interwell dynamic connectivity model, wherein the data points comprise the production data of the production wells in the block in the preset time interval. Stratum informationis reflected completely and accurately under the condition of the limited data points, and the connectivity coefficients among current stratum injection and production wells are truly reflected too.

Description

technical field [0001] The invention relates to the technical field of oil and gas field development, in particular to an input parameter analysis method and device for a dynamic connectivity model between multi-layer wells. Background technique [0002] Water injection development is the most widely used development method for most oilfields. When the oilfield is in the middle and late stages of development, it enters the stage of high water cut and ultra-high water cut. Due to reservoir heterogeneity, fluid mobility difference, and injection-production difference, etc., The dominant channel of water flow is gradually formed in the formation, which leads to the formation of a fixed seepage field, serious inefficient or ineffective water circulation, and the decline of formation water storage rate, which seriously affects the effect of water flooding development. The most important input parameters of the dynamic connectivity model between multi-layer wells are the water inj...

AI Technical Summary

Problems solved by technology

The number of data points directly determines the quality of the inversion results. If too few data points are obtained, the signal transmitted in the formation cannot fully and accurately reflect the formation information, which will affect the final solution result, and the interwell dynamic connectivity coefficient obtained cannot reflect the Real connectivity between injection and production wells

However, if too many data points are obtained, on the one hand, new requirements are put forward for the storage period of on-site production data; The dynamic connectivity relationship between wells may change. At this time, the dynamic connectivity coefficient between wells obtained by inversion is too much affected by the previous production data, and cannot truly reflect the connectivity coefficient between injection and production wells in the current formation.

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