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

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.

CO2 storage capacity estimation under geological uncertainty using 3-D geological modeling of unconventional reservoir rocks in Shahejie Formation, block Nv32, China

“…Carbon capture and storage is an alternative approach for minimizing CO 2 emissions to the atmosphere (Vo Thanh et al 2019;Ampomah et al 2017b). In general, CO 2 can be stored in different subsurface sites, such as deep saline aquifers, coal bed seams, unconventional resources, and depleted petroleum reservoirs (Vo Thanh et al 2020b, 2020a.…”

“…In general, CO 2 can be stored in different subsurface sites, such as deep saline aquifers, coal bed seams, unconventional resources, and depleted petroleum reservoirs (Vo Thanh et al 2020b, 2020a. Among these storage sites, saline aquifers have the largest CO 2 storage capacity (Vo Thanh et al 2019). However, depleted petroleum reservoirs are the most suitable candidates because the CO 2 injection process can improve oil recovery (Vo Thanh et al 2019).…”

Application of artificial neural network for predicting the performance of CO2 enhanced oil recovery and storage in residual oil zones

“…Carbon capture, utilization, and storage (CCUS) is the potential solution to slow down greenhouse gas emission and climate change 1 , 2 . CO 2 could be stored in many possible formations such as saline aquifers, depleted hydrocarbon reservoirs, depleted fractured shale formations, fractured basement reservoirs, and deep ocean formations 3 – 6 . Currently, Residual Oil Zones (ROZs) have been considered as promising formations for long-term geological CO 2 storage 7 .…”

Water vapor effects on CO2 separation of amine‐containing facilitated transport membranes (AFTMs) module: mathematical modeling using tanks‐in‐series approach

“…Mathematical modeling is a useful tool and has been used for evaluating the performance of CO 2 capture, 11,12 as well as CO 2 ‐enhanced oil recovery (EOR) and storage 13,14 . To improve the evaluation of membrane CO 2 capture for supporting the advancement of AFTMs, various modeling works on AFTMs have been carried out over the past decades.…”

“…Mathematical modeling is a useful tool and has been used for evaluating the performance of CO 2 capture, 11,12 as well as CO 2 -enhanced oil recovery (EOR) and storage. 13,14 To improve the evaluation of membrane CO 2 capture for supporting the advancement of AFTMs, various modeling works on AFTMs have been carried out over the past decades. For instance, Guha et al 15 proposed a model for facilitated transport of CO 2 through AFTMs, and effects of membrane thickness and CO 2 partial pressure have been numerically studied.…”