Integrated workflow in 3D geological model construction for evaluation of CO2 storage capacity of a fractured basement reservoir in Cuu Long Basin, Vietnam. (November 2019)

• Record Type: Journal Article
• Authors: Vo Thanh, Hung; Sugai, Yuichi; Nguele, Ronald; Sasaki, Kyuro
• Is Part Of: International journal of greenhouse gas control. Volume 90(2019)
• Publication Date: 2019-11
• Subjects: Artificial neural networks -- CO2 storage capacity calculation -- Integrated 3D geological model -- Fractured basement reservoir -- Cuu Long Basin; Greenhouse gases -- Environmental aspects -- Periodicals; Air -- Purification -- Technological innovations -- Periodicals; Gaz à effet de serre -- Périodiques; Gaz à effet de serre -- Réduction -- Périodiques; Air -- Purification -- Technological innovations; Greenhouse gases -- Environmental aspects; Periodicals; 363.73874605
• DOI: 10.1016/j.ijggc.2019.102826
• Languages: English
• ISSNs: 1750-5836

Abstract

Highlights: Constructing an integrated workflow for fracture basement reservoir which can be applied to other oil and/or gas field. Artificial Neural Network (ANN) is good algorithm to predict porosity and permeability values with reasonable accuracy. Sequential Gaussian Simulation (SGS) and co-kriging method are an effective method to distribute 3D petrophysical modeling. 3D geological modeling is an efficient way to evaluate the theoretical CO2 storage capacity. Abstract: Carbon dioxide (CO2 ) capture, utilization, and storage (CCUS) have been proposed as a possible technique to mitigate climate change. In this vein, CO2 storage through enhanced oil recovery (EOR) in depleted hydrocarbon reservoirs is touted as a most effective approach because it synergistically increases oil production and enables permanent sequestration into the reservoirs. However, the construction of a reasonable 3D geological model for this storage reservoir is a major challenge. Thus, this study presents an efficient workflow for constructing an accurate geological model for the evaluation of CO2 storage capacity in a fractured basement reservoir in the Cuu Long Basin, Vietnam. Artificial neural network (ANN) has been used to predict porosity and permeability values through seismic attributes and well log data. The predicted values were selected using high correlation factors with well log data. Subsequently, the Sequential Gaussian Simulation and co-kriging methods were applied to generate a 3D static geological model by using azimuth and dip parameters. Finally, drill stem test matching was performed to validate the accuracy of the porosity and permeability models through dynamic simulation. A validation 3D reservoir model, which integrates geophysical, geological, and engineering data from fractured basement formation in Cuu Long Basin, was further constructed to calculate theoretical CO2 storage capacity. As a result, the calculated storage capacity for the fractured basement reservoir ranged from 7.02 to 99.5 million metric tons. These estimated results demonstrate that fractured basement reservoir has a combined potential for CO2 storage and EOR in the Cuu Long Basin.