Development of Application for Identification of Hydrocarbon Prospect Zone In Well Logging Based on Fuzzy Logic

In the oil and gas industry, subsurface well log measurements are typically performed by geoscientists and petro physicists in exploration and production settings. Well logs provide valuable information on the petrophysical properties of underground petroleum reserves. However, random errors and noise during the acquisition process are prone to occur, causing the decision-making phase to be inaccurate. Although most of these problems can be solved today by using advanced acquisition techniques, there is a need for a proper algorithm to be developed to define an accurate hydrocarbon prospect zone. An application that is used for determining the contents zone of hydrocarbon in a drilling well has been developed based on fuzzy logic. This application can predict the hydrocarbon prospect zone as performed by experts. Fuzzy logic is used in the decision-making module by mapping input space into the output with respect to the hydrocarbon prospect zone. This study utilizes log measurements such as gamma ray, resistivity, neutron, and density to estimate the hydrocarbon prospect zone when raw logging procedures. The inference system that is used is Fuzzy Inference System (FIS) - Mamdani. Using test data from refinery wells in East Kalimantan, the proposed application achieves an accuracy level of 90.06%.