Quantitative evaluation method for oil column thickness based on fault screening

Abstract

The invention discloses a quantitative evaluation method for the oil column thickness based on fault screening. The quantitative evaluation method comprises the steps that reservoir forming geologicalfactors of a research area are analyzed, relevant basic drawings are compiled, and the basic drawings and an oil reservoir are superimposed in pairs to define main control factors of oil reservoir distribution; and the found oil column thicknesses in the research area are counted and are in fitting with the main control factors for affecting oil reservoir distribution, and the main control factors of the oil column thickness are defined. The main control factors of the oil column thickness are the fault mudstone scraping ratio, the reservoir inclination angle, and the included angle of the fault trend and principal stress. The three characterization parameters, namely the fault mudstone scraping ratio, the reservoir inclination angle, and the included angle of the fault trend and the principal stress, and the oil column thickness are subjected to multiple regression through mathematical statistic package for social science (SPSS), and a quantitative prediction mathematical model of the oil column thickness is obtained for judging. The quantitative evaluation method has the beneficial effects that the reliability and accuracy of oil and gas resource evaluation and well position optimization deployment can be improved.

Description

technical field [0001] The invention belongs to the technical field of geological exploration of oil and gas resources, and relates to a method for quantitatively evaluating the oil-bearing height of oil reservoirs based on fault shielding. Background technique [0002] Reservoir oil-bearing height prediction is of great significance for oil and gas resource evaluation and well location optimization deployment. Scholars have carried out a lot of fruitful research on this, and formed some research ideas and prediction methods on the oiliness of traps. However, these methods are mostly aimed at lithologic-stratigraphic reservoirs. For example, Ning Fangxing (2010) used SPSS software to perform multiple regression on the factors affecting the oil-bearing height of stratigraphic reservoirs, and established a fitting formula for oil-bearing height; Based on the analysis of the relationship with the single factor, the multi-parameter fitting relational expression of the oil-beari...

AI Technical Summary

Problems solved by technology

Fault-shielding reservoirs (fault-block reservoirs, fault-nose reservoirs) are widely developed reservoir types in oil-gas-bearing basins in my country, and their oil-bearing height has become an important parameter that has attracted wide attention. The current evaluation methods are mostly based on the oil wells that have been drilled. combined with the qualitative prediction of geological conditions, it is difficult to meet the needs of fine exploration; Wang Chao (2011) used the analytic hierarchy process to establish the quantitative relationship between the oil-bearing height of fault-block reservoirs and the main controlling factors, but the main controlling factors considered There are too many factors, and the assignment of weight coefficients is relatively random, resulting in a large error between the predicted value and the actual value, which lacks applicability and generalization

Therefore, the current prediction of the oil-bearing height of fault-shielding reservoirs is still in the qualitative-semi-quantitative stage, and the accuracy is not enough, which greatly restricts the effective exploration and development of this type of reservoirs

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