Lithofacies "sweet spots" prediction method and system for shale reservoirs

Abstract

An embodiment of the present invention provides a method and system for predicting the lithofacies "sweet spots" of shale reservoirs. The method includes: according to the intersection relationship between the lithofacies attribute parameters of shale reservoirs and the daily oil production per meter, the The attribute parameters related to oil production per meter include: quartz mineral content, feldspar mineral content, calcite mineral content, clay mineral content, lithology, lithofacies, porosity, permeability; based on the obtained attribute parameters, the construction of mud shale reservoir A comprehensive prediction and evaluation model for lithofacies "sweet spot"; comprehensively judge the lithofacies "sweet spot" of shale reservoirs based on the comprehensive prediction and evaluation model and the daily oil production per meter. By applying minerals, lithology, and lithofacies as evaluation indicators to the prediction of reservoir lithofacies "sweet spots", it can intuitively and clearly indicate the quality of reservoirs, which can save time in the process of oil and gas exploration and development, improve efficiency and precision.

Description

technical field [0001] The present invention relates to the field of oil and gas exploration and development, and more specifically, to a method and system for predicting lithofacies "sweet spots" of shale reservoirs. Background technique [0002] The comprehensive prediction and evaluation method of lithofacies can predict high-quality shale reservoirs, identify favorable intervals and "sweet spot" layers, and play an important role in guiding the next step of exploration and development. [0003] At present, there are mainly three methods for the comprehensive evaluation of logging lithofacies in shale reservoirs: one is the gray correlation analysis method, which first quantifies the relationship between the factors, and calculates the weight of each primary and secondary factor. Finally, the comprehensive evaluation factor is obtained. This method greatly guarantees the objectivity of parameter weight determination. However, its data source comes from foreign oil and gas...

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Problems solved by technology

[0003] At present, there are mainly three methods for the comprehensive evaluation of logging lithofacies in shale reservoirs: one is the gray correlation analysis method, which first quantifies the relationship between the factors, and calculates the weight of each primary and secondary factor. Finally, the comprehensive evaluation factor is obtained. This method greatly guarantees the objectivity of parameter weight determination. However, its data source comes from foreign oil and gas reservoir exploration and development data, which is not suitable for domestic shale reservoir lithofacies evaluation; the other is The analytic hierarchy process is used to evaluate reservoirs in grades by establishing a hierarchical structure model and constructing a judgment matrix. This method is too broad, mainly for reservoir evaluation, and lacks a specific index model; The fuzzy mathematical method assigns weights to the factor indicators at all levels, and then establishes a multi-level fuzzy mathematical evaluation model to evaluate the reservoir. This method is similar to the gray correlation method, but the disadvantage is that the evaluation is not accurate and requires many parameters.

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