Browsing by Author "Boateng, Cyril D."
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- ItemBiogenically modified reservoir rock quality: A case from the lowermost member Paleocene Funing Formation, Gaoyou Depression, Subei Basin, China(Journal of Petroleum Science and Engineering, 2022) Quaye, Jonathan Atuquaye; Jiang, Zaixing; Liu, Chao; Adenutsi, Casper Daniel; Boateng, Cyril D.; 0000-0002-1721-4158Bioturbation can influence reservoir quality and is consequential to the producibility of a reservoir. The study of samples from the lowermost member of the Paleocene Funing Formation (E1f1), Gaoyou Depression, Subei Basin, shows how bioturbation affects reservoir quality. Techniques used to study the samples include petrography, pressure decay porosimetry, pulse decay permeametry, Field Emission Scanning Electron Microscopy, and Energy Dispersive X-ray Spectroscopy. Sample A is intensely burrowed by Taenidium, Scoyenia, Skolithos, Palaeophycus, and other trace fossils. Increased isotropy in sample A contributes to cleaner well-sorted burrows, relative to its surrounding matrix, and 67.18% augmented burrow porosity. Taenidium and Palaeophycus in sample B indicate 20.23% improved burrows porosity. Plant debris and/or root traces in sample C have a 3.68% reduction in porosity. In samples A and B, the arithmetic mean of permeability describes all horizontal fluid flows within burrows. In sample C, the geometric mean of permeability describes the fluid flow in all directions. Porosity is ≤ 11.2%, permeability ≤1 md in samples, and sample C log-derived porosity ≤0.33%. This study demonstrates that bioturbation together with depositional factors (sorting, grain size distribution, and mud matrix/burrow content) and diagenetic modifications (albitization, compaction, dissolution, kaolinization, and precipitation) control the quality of the high to intensely bioturbated (Bioturbation Index 4 to 5; 61–99 vol %) sandstone and siltstone reservoir facies of the E1f1.
- ItemCharacterization of complex fuvio–deltaic deposits in Northeast China using multi‑modal machine learning fusion(Scientific Reports, 2020) Boateng, Cyril D.; Fu, Li‑Yun; Danuor, Sylvester K.; 0000-0002-1721-4158Due to the lack of petroleum resources, stratigraphic reservoirs have become an important source of future discoveries. We describe a methodology for predicting reservoir sands from complex reservoir seismic data. Data analysis involves a bio-integrated framework called multi-modal machine learning fusion (MMMLF) based on neural networks. First, acoustic-related seismic attributes from post stack seismic data were used to characterize the reservoirs. They enhanced the understanding of the structure and spatial distribution of petrophysical properties of lithostratigraphic reservoirs. The attributes were then classifed as varied modal inputs into a central fusion engine for prediction. We applied the method to a dataset from Northeast China. Using seismic attributes and rock physics relationships as input data, MMMLF was performed to predict the spatial distribution of lithology in the Upper Guantao substrata. Despite the large scattering in the acoustic-related data properties, the proposed MMMLF methodology predicted the distribution of lithological properties through the gamma ray logs. Moreover, complex stratigraphic traps such as braided fuvial sandstones in the fuvio–deltaic deposits were delineated. These fndings can have signifcant implications for future exploration and production in Northeast China and similar petroleum provinces around the world.
- ItemEvaluation of porosity and permeability of sandstones within the Oti Group of the Volta Basin using petrophysical and petrographic techniques(Journal of the Ghana Institution of Engineering, 2023) Zobah, Theresa N.; Adenutsi, Casper D.; Amedjoe, Godfred C.; Wilson, Matthew C; Mensah, Emmanuel; Boateng, Cyril D.; Sarpong, Kwame K.; Opuni, Lydia N. O.; Danuor, Sylvester K.; Karimaie, Hassan; 0000-0002-1721-4158This study investigates the reservoir quality of sandstones in the Oti Group of the Volta Basin of Ghana. Geological field mapping, petrographic, petrophysical, mineralogical, and geochemical techniques are used to investigate the reservoir parameters of the sandstones by evaluating the fluid holding and transmission capabilities of the rocks. Results from the comprehensive study identified two sandstone formations of interest; viz. the Bimbila Sandstone and Yabraso Sandstone. Both sandstones were found to be quartz sandstones (sub-arkose and quartz arenites). The Bimbila Sandstones proved to have better porosity and permeability as compared to the Yabraso Sandstones. The Yabraso Sandstone showed porosity between 7-22 % with an average porosity of 13 % (helium gas) and permeability of 63.41 mD, which may be linked to intense cementation and intermediate compaction as well as grain size, shape and arrangement. The Bimbila Sandstones showed better porosity and permeability with a porosity range of 6-24 %, an average porosity of 14 % (helium gas) and 131.80 mD permeability. This is seen to be due to lower compaction supported by framework-stable quartz resulting in a well-connected pore system with high permeability. Further mineralogical data show that the clay minerals present are in minor concentrations. Also, the position of the Yabraso and Bimbila Sandstones in the project area as plotted on the geological map show that there is a close proximity relationship between these sandstones and the limestones; hence forming a conducive system such that if hydrocarbons are produced by the possible source rocks (limestones), they can be housed by the sandstones.
- ItemRock type prediction and 3D modeling of clastic paleokarst fillings in deeply-buried carbonates using the Democratic Neural Networks Association technique(Marine and Petroleum Geology, 2021) M'endez, Jos´e N.; Jin, Qiang; Zhang, Xudong; Gonz'alez, Maria; Kashif, Muhammad; Boateng, Cyril D.; Zambrano, Miller; 0000-0002-1721-4158This study outlines a probabilistic model based on artificial neural networks applied to the deeply-buried karsted carbonates of the Ordovician Yingshan Formation, which represent significant oil reservoirs in western China. The complexity of both rock type prediction and 3D facies modeling of paleokarst fillings, which are hosted within the cavities, drives the need to apply innovative techniques for identifying new oil plays. Due to the high heterogeneity of clastic fillings and patchy continuity of the karst patterns, physical evaluation of these reservoirs is extremely complex. We propose the Democratic Neural Networks Association (DNNA) as the probabilistic technique to solve these challenges. This technique simultaneously runs several artificial neural networks in parallel and combines seismic data and well logs. The resulting probable facies volume is expected to provide an appropriate distribution and delineation of clastic fillings (i.e., conglomerates, fine-grained sandstones, silt stones, mudstone, dolomite fragments, and sparry calcarenite) and unfilled or empty spaces. This calculated volume is then used as a reliable input data to condition trend analysis on a very fine geological grid, in order to model the complex patterns in question. The static model obtained shows that, the probabilistic distribution of each filling has the same orientation as karst system. Likewise, spatial dimensions similar to the proposed analogue model of these patterns (vertical and horizontal scales) are delineated. Finally, we validated prediction results by comparing them with the interpreted karst facies of a well not initially considered in the 3D model. The results indicating that the DNNA technique proves to be a useful innovative tool for generating realistic de pictions of fillings deposited within deeply-buried paleokarst.
- ItemUnderrepresentation of Local Researchers in Geophysical Studies at the Bosumtwi Impact Crater: Insights from A Systematic Review(Scientific African, 2023) Boateng, Cyril D.; Akrugu, Christopher A.; Wemegah, David D.; Danuor, Sylvester K.; 0000-0002-1721-4158Impact cratering is an important aspect of planetary evolution. Geophysics plays a complementary role in identifying impact craters on Earth given the non-unique geological characteristics associated with such craters. The Bosumtwi impact crater in Ghana represents one of the world’s most well-preserved and young mid-sized impact craters, and this study aims to evaluate the current state of geophysical research conducted in this area. The Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) technique was employed for data collection and analysis, which involved identifying and screening relevant sources of data. Results indicated that the maximum number of publications (14) on the Bosumtwi impact crater was recorded in 2007, with 15% of these articles being affiliated with Ghanaian institutions. Furthermore, only two articles reported funding from Ghana. The major geophysical methods applied in studies of the Bosumtwi impact crater include various techniques that have confirmed the presence of shock metamorphosed rocks. Although geophysical methods cannot provide unambiguous evidence for an impact origin of the Bosumtwi crater, they did provide additional constraints in estab lishing its impact origin. This study highlights the lack of local financial support for research in Ghana and African countries in general, with the underrepresentation of Ghanaian geophysical researchers being a concerning outcome. The absence of hazard studies such as the creation of unstable cliffs and the long-term effects of the meteorite impact on inhabitants of the Bosumtwi impact crater is particularly significant. Further research is necessary to fully understand the implications of this underrepresentation. Moreover, this study highlights the importance of research at the Bosumtwi impact crater for achieving the UN Sustainable Development Goals.