ANALYSIS OF GAS RESERVOIR DISTRIBUTION IN ‘MANTAW’ FIELD, KAMPUNG BARU FORMATION, KUTAI BASIN USING SIMULTANEOUS INVERSION METHOD

• Main Author: Marciano Zola, Alfredo
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/43920
• Institution: Institut Teknologi Bandung

Hydrocarbon, especially oild and gas are still the main source of energy for daily life in recent. Eventhough alternative energy are being explored and developed, for example: geothermal, coal, nuclear, etc, but still mankind rely on oil and gas. The high in demand followed by decreasing production (Statistik Pertambangan Minyak, dan Gas Bumi, 2017). Because of that, we need to reevaluate amd develop our oil and gas field in Indonesia. One of those fileds are ‘Mantaw’ Field in Kutai Basin as an oil producing field ‘Mantaw’ Field is a gas producing field with clastic reservoir rock. AVO modelling has been done in this area and the result is AVO class 3 sand. The reservoir are separataed by non reservoir based on rock physics properties, in this case PImpedance and Poisson Ratio. These parameters concluded from the cross plot Then, seismic data that consists of 4 angle stacks: Near, Mid, Far, and Ultra far stacks are aligned before used to optimize the inversion result. These aligned cubes used to generate inversion wavelet using deterministic metrhod with extended white algorithm. Each well used in generating wavelet then the wavelet will be averaged to give the best wavelet for each angle stack. After that the low frequency model built by extrapolating the log parameters from wells used for inversion and horizon that already interpreted before. With Low Frequency Model has been built and inversion wavelet has been generated, than inversion could be done. The result of the inversion is two cube, inverted IP and inverted PR. From these cubes, inverted IP log and inverted PR log will extracted to do lithology analysis. Lithology analysis is step to determine the probability of a certain point with certain value of IP and PR to be gas sand. Using that classification, gas sand probability cube will be generated. The distribution of gas sand could be identified by analyzing this gas sand probability cube