PEMETAAN FASIES SEISMIK 3D NEURAL NETWORK UNTUK IDENTIFIKASI JEBAKAN HIDROKARBON (STUDI KASUS DAERAH TANGKAHAN LAGAN)

• Main Author: Samodra, Ari
• Format: Theses
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/4881
• Institution: Institut Teknologi Bandung

Abstract:<p align=\"justify\"> <br /> Tangkahan Lagan productive field is structural geologic trap which has been proven to contain oil being produced. In the development process, this field has various constrains due to 7 dry wells, wich caused the uncertainty of play concept of this area. Based on 2D seismic data, this problem is unsolved, therefore-3D seismic survey is conductive.<p align=\"justify\"> <br /> Interpretation technology applied in this area uses Neural Network Technology (NNT) approach. NNT is a new technology breaktrough namely seismic interval classification process which is adapted to interpretation horizon in 3D volume based on seismic wiggle traces. This concept is seismic facies analysis which can represent & be compared to geological condition. Interpretation method - which is applied to get optimum precision or accuracy - is conducted with seed correlation, propagation, manual, and interpretation lines networking design.<p align=\"justify\"> <br /> Evaluation result gives an image of better play to increase the field\'s performance. The presence of dry holes can be evaluated and new wells location in new prospects can be defined from this evaluation result. It can be predicted that there is a lateral facies changes influence and small fault control wich influence the hydrocarbon trap distribution.