A great portion of the world’s oil reserves is contained in naturally fractured reservoirs. As the conventional oil and gas reservoirs have become significantly depleted whereas energy demand is sharply increases, NFRs play an important role in oil exploration and makes a large contribution toward oil and gas production worldwide. However, characterization of fractured reservoir is very complex as compared as conventional reservoirs. Lacking of experiences during production stages may quickly destroy entire reservoir. Therefore, the successful case studies as well as failure lessons should be highlighted for improving recovery efficiency in such complex reservoirs. This paper aims to introduce two historical case studies of successful development plan for giant fractured granite basement reservoirs in Viet Nam. These reservoirs contain huge hydrocarbon resources in basement source rock and present a unique geological characterization, very high heterogeneity, high temperature and closure stress. A detailed geological understanding of the reservoir, along with a creative reservoir simulation, is needed to determine the optimal recovery method for these reservoirs. These are the keys to having a successful operation, as well as reducing uncertainties and achieving the most efficient of oilfield management. With a large database collected from over twenty years of production period of over 215 wells, the authors developed a workflow for integrating between static and dynamic data. The geological characterization of two typical basement reservoirs was thoroughly analyzed to figure out their effect on recovery schemes. A new approach for building geological model by artificial neuron network technique was introduced, and these integrated results have been served as input data for simulation with IMEX in CMG simulator. Based on the reservoir modeling, we proposed a promising method for improving oil recovery factor by optimizing the well network locations, application of horizontal well and gaslift. From our historical experiences, the authors introduce the most appropriate method for overcoming the challenge of waterflooding operation and stimulation for fractured basement reservoirs.
The Cuu Long Basin is one of the Tertiary sedimentary basins situated on the continental shelf of Vietnam, which demonstrates the high potential of oil and gas. Apart from fractured granite reservoirs, the Oligocene - Miocene sand bodies are thought to have significant potential for forming non - structural traps. The results of the study on the composition and physical properties of the sediments derived from wells "X" and "Y", block 09 - 1, Cuu Long Basin show that there is a clear difference between the Late Oligocene and Early Miocene sandstone in the well "X", namely the Miocene sandstone shows larger particle size, higher roundness and sortness (TB: 434.2; Ro: 0.69; So: 2.22) than those of the Late Oligocene sandstone (TB: 104.28; Ro: 0.64; So: 1.46). This difference is likely attributed to the fact that the Miocene sandstone was influenced by the marine environment, which intensified the roundness and sortness. Meanwhile, the well "Y" did not show much difference in the physical parameters of the sediments between the Late Oligocene and Early Miocene age ranges. However, the grain size was slightly increased and the roundness was less during the Early Miocene. It is possible that the “Y” well is located closer to the local source. The variation in the physical parameters of the sediments, proportion of sand grains and clay minerals shows that the quality of late Oligocene reservoir is better than that of Early Miocene reservoir, and the Late Oligocene reservoir quality in the "X" well is better than that in the borehole "Y".
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.