Research and application of reservoir productivity prediction in metamorphic buried hill based on multi-dimensional model

Abstract With the large-scale development of metamorphic buried-hill reservoirs in Bohai, the effective evaluation and prediction of reservoir availability and productivity has become the key to the development of metamorphic buried-hill reservoirs. Due to the characteristics of multiple factors affecting the availability and productivity of metamorphic buried-hill reservoirs and unclear mechanism models, the productivity difference between Wells is large and the development effect is limited. In this paper, a method based on big data statistics is used to synthesize the drilling, recording and logging data on the basis of single parameter evaluation, and the coupling interpretation chart of metamorphic rock record measurements under multi-parameter of acoustic imaging and array acoustic wave is used to quickly classify and evaluate the variable quality reservoir. Through principal component analysis, data dimensionality reduction, variable regression optimization, coupling iteration parameter optimization, etc., the quantitative relationship between productivity and comprehensive evaluation indexes of reservoir logging is established, and the effective prediction and evaluation of about 88% coincidence degree is achieved, which lays a solid geological foundation for efficient and scientific development of metamorphic buried-hill oil and gas reservoirs.