by Ukpebor Osahon and Maju-Oyovwikowhe Gladys Efetobore
Original Research
This study focuses on the reservoir characterization of the UM field in the Niger Delta using Amplitude Versus Offset (AVO) analysis. The study integrates various data sources, including 3D seismic data, well deviation survey data, and checkshot survey data, to gain a comprehensive understanding of the reservoir properties. The AVO analysis involved cross-plotting gradient against intercept values derived from the AVO analysis, revealing an anomalous deviation from the background trend. The identified Class IV AVO anomaly suggests the presence of a gas sand reservoir within the study interval. The seismic stacks and attribute slices confirm the amplitude variations at different offsets, further supporting the identification of the gas sand reservoir. The results provide valuable insights into the reservoir's seismic response, as indicated by the amplitude variations observed in the seismic stacks. Additionally, the AVO analysis allows for the assessment of lithological variations within the reservoir. The cross-plot of gradient and intercept values aids in understanding the reservoir's fluid content, as different combinations of these parameters correspond to specific lithologies and depositional environments. The findings of this study have significant implications for reservoir evaluation and exploration activities. The identification and characterization of the gas sand reservoir using AVO analysis contribute to a better understanding of the subsurface properties in the UM field. This knowledge can guide future drilling and production decisions, leading to more effective reservoir management and hydrocarbon recovery strategies.
Journal of Geosciences and Geomatics. 2023, 11(2), 56-66. DOI: 10.12691/jgg-11-2-3
Pub. Date: June 19, 2023
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by Maju-Oyovwikowhe Gladys Efetobore and Ukpebor Osahon
Original Research
The aim of this study is to comprehensively characterize the reservoir and analyze the fluid behavior in the Majosa field located in the Niger Delta. The investigation involved the interpretation of well logs, fluid replacement modeling, and the generation of synthetic seismograms for well-to-seismic tie analysis. Interpretation of the well logs yielded valuable insights into the subsurface characteristics of the study interval. The gamma ray log successfully identified lithology, with leftward deflections indicating sand layers and rightward deflections indicating shales. The neutron-density overlay revealed a balloon structure in the reservoir, suggesting the presence of gas within the study interval. Moreover, the high resistivity kick and low water saturation further supported the existence of gas. Shale intercalations were observed within the reservoir sand, confirming the study interval to be within the Agbada Formation. The reservoir sand was located at an approximate depth of 3,392m, exhibiting 22% porosity and 18% water saturation. To assess log behavior and determine the real fluid composition indicated by the neutron-density overlay, fluid replacement modeling employing Biot-Gassmann's equations and the FRM function in Hampson-Russel Software was conducted. A two-phase fluid model (80% oil, 20% brine) accurately captured the S-wave behavior associated with gas sand observed in the logs. P-wave, S-wave, and density logs exhibited significant changes during the two-phase fluid replacement model. A synthetic seismogram was generated using a statistical wavelet derived from the fluid replacement model logs. The well-to-seismic tie achieved a correlation coefficient of 60.5%, improving subsurface interpretations. This study identified lithology, porosity, and the presence of gas, which impact exploration and production activities. It enhances reservoir management and development planning, emphasizing the potential for enhanced hydrocarbon recovery and the importance of gas monetization strategies. The comprehensive reservoir characterization and fluid analysis inform production optimization and maximize hydrocarbon recovery.
Journal of Geosciences and Geomatics. 2023, 11(2), 39-55. DOI: 10.12691/jgg-11-2-2
Pub. Date: June 19, 2023
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by Reuben Phiri, Wallace Mukupa, Foster Lubilo and Alick R. Mwanza
Original Research
The economic growth that Zambia seeks to attain calls for alternative sources of energy besides hydroelectricity which has proved inadequate due in part to climate change. One such form of alternative energy is geothermal energy. Various research has been undertaken on the feasible way of harnessing geothermal energy using different methods such as thermal, electrical, magnetic and seismic methods. But exploring for potential sites was still a challenge. One way round this challenge was to devise a method that first identifies potential geothermal sites instead of relying on trial and error scenarios. This study used gravity data obtained by the European Space Agency (ESA) through Global Monitoring for Environment and Security (GMES) project. This data was used to calculate gravity disturbances of the earth’s crust in order to understanding density variations in the subsurface geology. This study therefore, used the density variations in the subsurface geology to map potential geothermal sites at a scale which makes it feasible and economical for geophysicists and geologists to have a starting point in exploring for geothermal energy. In so doing, this study devised an economical method of mapping potential geothermal sites using the freely available gravity data by assessing the accuracy of the gravity data using mean sea level elevations, mapping gravity disturbances and relating them to thermal imagery, geological and land use maps to produce potential geothermal site maps at feasible and economical scale. This study found that the use of hot springs as an indication of potential geothermal sites was not accurate and definitely not a right basis for investigating geothermal resources. Potential geothermal sites were found to lie within the rift valley where temperature are high and where the earth’s crust density is low in addition to faulting.
Journal of Geosciences and Geomatics. 2023, 11(2), 33-38. DOI: 10.12691/jgg-11-2-1
Pub. Date: May 18, 2023
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