Predication method of outer-source entrapment fullness degree

Abstract

The invention relates to a predication method of the outer-source entrapment fullness degree. The method comprises the steps that nine geological factors of entrapment depth, a sand body inclination angle, sand body volume, fault sealing performance, distance between entrapment and an oil source fault, cover layer thickness, cover layer quality, cover layer mobility and residual pressure which are relevant to the outer-source entrapment fullness degree are selected; entrapment with the same oil deposit type under the same structural setting is selected, the nine factors and the computed fullness degree of the entrapment are obtained respectively, scatter diagrams are drawn respectively, and the relation of a single factor and the entrapment fullness degree is obtained through a fitting function; through multiple linear regression, a predication model of the entrapment fullness degree is established for the single factor relation; and model testing and correction are carried out. The predication model is high in pertinence, under the same structural setting, identical oil deposit type entrapment predication accuracy is high, the technical problem that outer-source entrapment fullness degree predication is hard is solved, the unknown outer-source entrapment fullness degree can be predicted in a quantitative mode, and significance is achieved in guiding of oil gas exploration and deployment.

Description

technical field [0001] The invention relates to a method for predicting oil and gas, in particular to a method for predicting the fullness of oil and gas in unknown source traps by comprehensive geological parameters. Background technique [0002] Prediction of trap fullness is an important part of petroleum exploration. Before drilling, in order to avoid failure of exploration wells, it is often hoped to accurately predict the oil and gas of traps. [0003] At present, there are many methods for predicting the hydrocarbon-bearing properties of traps, including geological risk probability method, mathematical statistics method, fuzzy evaluation method, neural network method, gray system method, stratigraphic analysis method, and geophysical method. The classification and summary of geological parameters, and the establishment of corresponding formulas to predict the oil and gas of traps, but there are few predictions for oil and gas enrichment strata and oil and gas reservoi...

AI Technical Summary

Problems solved by technology

[0006] In addition, the predecessors have summarized and improved the relatively complete prediction method of oil and gas in source traps, and summarized the geological parameters that affect the oil and gas of in-source traps, but have not yet established a prediction model for the fullness of out-of-source traps. For the enrichment area, most of the oil and gas are mainly distributed outside the source, that is, other source oil and gas reservoirs, the accumulation conditions are complex and changeable, the influencing factors are different, and the prediction is difficult

On the other hand, the subsurface geological conditions are complex and affected by geological factors such as structural belts and oil and gas reservoir types. The fullness of source traps is not only affected by a single factor, but the result of multiple factors. Static conditions, migration, preservation and other dynamic conditions may all be factors affecting the fullness of traps, and there may be multiple parameters that characterize the same condition. It is difficult to accurately predict the fullness of different traps with a general normalized formula

[0007] At present, there is no suitable method to predict the fullness of other source traps

Images