Study the CO2 Injection and Seques- tration in Depleted M4 Carbonate Gas Condensate Reservoir, Malaysia.

Published on Carbon Management Technology Conference Orlando, Florida 2012

The paper discussed about how a depleted gas field located offshore Sarawak can be a potential candidate for CO2 sequestration site in conjunction with another high CO2 field development and commercialization efforts. The study covered 20 years of gas production history and forecast fol- lowed by 10 years of CO2 injection in the selected optimum scheme and then monitoring part more than for 100 years after injection to assure the safe sequestration and potential CO2 leakage.

Behind Casing Opportunity BCO of Poor-Quality Reservoir - Unlocking a Mature Offshore Province

Published on Carbon Management Technology Conference Orlando, Florida 2012

Behind casing opportunity (BCO) is an important production enhancement solution that extends field life in brownfield development, specifically at low oil prices and the current cost control environment. BCO potentially offers, low-hanging fruit in terms of cost and realizing cheap oil, but successful maturation and realization of these opportunities rely on a clear understanding of reservoir behavior and uncertainties. The approach focuses on the impact of workflow optimization, multidisciplinary and integrated work on instantaneous production gain. The sequential workflow includes data gathering, proper data preparation, and integrating basic data and information (brilliant at the basics) to reduce inherent risk and uncertainty. The result demonstrates the huge upside potential for nominated low resistive pay zones that can be developed through BCO or horizontal infill targets.

Integration of knowledge-based seismic in- version and sedimentological investigations for heterogeneous reservoir

Published on Journal of Asian Earth Sciences 202 (2020) 104541

A knowledge-based seismic acoustic impedance inversion method and a rule-based artificial intelligence method was introduced for porosity estimation. Using artificial intelligence method, precision of porosity model had been improved. The rules and the knowledgebase are authoritative to be used in other case studies. The method- ology is proper for heterogeneous reservoir with spatially sparse wells.

Machine Learning model to predict the contact of angle using mineralogy, TOC and process parameters in shale

Published on EAGE Asia Pacific Virtual Geoscience Week 2021

The study aims to investigate the effect of both parameters, TOC, and mineralogy on shale wettability with a case study of Malaysian shale samples. The values for each parameter, TOC, and mineralogy are obtained through thermal pyrolysis and X-ray diffraction, respectively. Advance application is carried out by applying the machine learning technique to predict the effect of shale TOC and mineralogy on the wettability of the reservoir rock. The developed model has been successful in predicting the contact angle for different input variables of the machine learning model with high r squared values.