摘要
Tight sand gas reservoirs are our country’s fairly rich unconventional natural gas resources, and their exploration and development is of prime importance. Sulige Gas Field which located in the northern Ordos Basin is tight sand gas reservoirs. It is typically featured by low porosity and low permeability, and the error of porosity calculation by traditional methods is larger. Multicomponent explanation model is built by analyzing the thin slice data, and the objective function is got according to the concept of optimization log interpretation method. This paper puts the Genetic Algorithm and the Complex Algorithm together to form the GA-CM Hybrid Algorithm for searching the optimal solution of the objective function, getting the porosity of tight sandstone gas reservoirs. The deviation got by this method is lesser compared with the core porosity, with a high reliability.
Tight sand gas reservoirs are our country’s fairly rich unconventional natural gas resources, and their exploration and development is of prime importance. Sulige Gas Field which located in the northern Ordos Basin is tight sand gas reservoirs. It is typically featured by low porosity and low permeability, and the error of porosity calculation by traditional methods is larger. Multicomponent explanation model is built by analyzing the thin slice data, and the objective function is got according to the concept of optimization log interpretation method. This paper puts the Genetic Algorithm and the Complex Algorithm together to form the GA-CM Hybrid Algorithm for searching the optimal solution of the objective function, getting the porosity of tight sandstone gas reservoirs. The deviation got by this method is lesser compared with the core porosity, with a high reliability.
