Identifikasi Keberadaan Hidrokarbon Menggunakan Inversi Impedansi Akustik dengan Algoritma Artificial Neural Network (ANN) - Maulana, Ansar; Lepong, Piter; Sutaji Putri, Devina Rayzy Perwitasari; Munir, Rahmiati (Geophysics Study Program, Faculty of Mathematics and Natural Sciences, Mulawarman University, 2024)
Hydrocarbons are the main energy source in the world, especially in Indonesia, this is what makes hydrocarbons a natural resource that has been extensively explored to determine the presence of hydrocarbons. The exploration used is the Geophysics method, namely the seismic method and the well logging method, both methods are processed to provide an overview of the subsurface. The data processing technique used is acoustic impedance inversion modeling which aims to determine the characteristics of the reservoir based on changes in the acoustic impedance value in each layer. In this study using model-based acoustic impedance inversion using an artificial neural network (ANN) algorithm and the results obtained in the inversion analysis obtained an error of 0.002, so that the model can be used on seismic trace data to produce an acoustic impedance model. modeling section with a value of less than 5000 which may mean that there are hydrocarbons in the research location. Keywords: Artificial Neural Network, Hydrocarbons, Acoustic Impedance, Inversion.