#TITLE_ALTERNATIVE# - (NIM 12208003); Pembimbing: Dr. Ir. Sudjati Rachmat DEA., SUWONDO
Hydraulic fracturing is one type of well stimulation which is most commonly used today. Hydraulic fracturing aims to increase the reservoir permeability by forming the fracture around the wellbore. The fracture was created by inject the high viscosity fluid into wellbore over its fracturing formation pressure. Before doing the hydraulics fracturing, usually done using specific software simulations to see possible fracture occurred. It aims to optimize the stimulation cost so that get the fracture desired results with an economical cost. Field K is old field which has many production wells that have been stimulated. Stimulation type that is done on the field K is Hydraulic fracturing because field K has small amount of its reservoir permeability so it needs fracture to increase the reservoir permeability. A large number of well that have been fractured by Hydraulic fracturing make this field has a lot of hydraulics fracturing data that will be the main data source of this study. This research performs a stimulation process that generates relationships among Hydraulic fracturing technical parameters with the geometry of the formed fracture. This relationship made by combining the theory of fuzzy logic with artificial neural network that will be called with Adaptive Neuro fuzzy Inference System (ANFIS). Results of this research aims to create relationship between the Hydraulic fracturing technical parameters with fracture geometry that occurred based on hydraulics fracturing data that has ever done on the field K. This relationship then validated with the simulation results from software. The resulting error of its relationship was very small. This Model was created as a quick description of fracture geometry.