High water cut later oil reservoir flow field grading evaluation method

Abstract

The invention relates to a high water cut later oil reservoir flow field grading evaluation method and belongs to the field of numerical reservoir simulation application and oil-gas field developmentflow field reconstruction. The high water cut later oil reservoir grading evaluation method comprises the steps that surface flux serves as a unique index for representing a flow field, firstly, clustering is carried out on the surface flux through a fuzzy c-means algorithm, a clustering center and a clustering number are obtained, a large parabolic membership function is used for carrying out normalization processing on surface flux data, a processing result is defined as flow field strength, the flow field strength is graded through the fuzzy c-means algorithm, and a complete flow field evaporation system is established. According to the high water cut later oil reservoir flow field grading evaluation method, a method support is provided for predicting remaining oil distribution, findinga preferential channel, quantitatively evaluating the flow field strength and directing digging potential remaining oil of a high water-cut stage oil field.

Description

technical field [0001] The invention relates to a method for graded evaluation of reservoir flow field in the late stage of high water cut, which belongs to the field of reservoir numerical simulation application and oil and gas field development flow field reconstruction. It performs quantitative graded evaluation on the dynamic parameters of reservoir flow field reconstruction, and establishes a method A grading evaluation method based on surface flux non-subjective factor control. Background technique [0002] Reservoir is a flowing field, and the flow of reservoir fluid can be characterized by flow field. The characterization and evaluation of the flow field has gradually become the focus of research in recent years. There is a lack of related research in foreign countries, and domestic research mainly focuses on the selection and evaluation methods of flow field characterization indicators. The selected indicators play a decisive role in the evolution of the flow field....

AI Technical Summary

Problems solved by technology

At present, some scholars have comprehensively analyzed the static and dynamic factors affecting the reservoir flow field, and used logical analysis to screen out the final water flux as the only indicator for flow field evaluation. However, in the process of characterization Human factors are relatively large. Most researchers artificially formulate the number of classification categories and upper and lower limits based on experience and laws. There are generally certain errors and the results are uncertain.

Therefore, this characterization method cannot objectively evaluate the flow field, and is not universally applicable to the characterization of the flow field in the late stage of high water cut. Therefore, it is urgent to find a set of non-subjective factor-controlled hierarchical evaluation methods to systematically characterize the oilfield flow field in the late stage of high water cut. system

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