The study is focused on the use of 3D seismic, well logs and checkchots data to delineate, evaluate and characterize reservoirs relating to their hydrocarbon potentials. Four localized wells were available for this study. The study location is Onka field, offshore, Niger Delta. Well correlation and detailed petrophysical analysis was carried out along all the wells. Three reservoirs were discerned within the agbada formation. Among these delineated reservoirs, reservoir 2 occurs to be the most prolific with average gross thickness of about 49ft, net pay thickness of about 43ft, average net to gross thickness of approximately 71%, a good porosity of 20% and hydrocarbon saturation of 81% which is more blatant in well DESLA 1ST2. Seismic interpretation shows the presence of 26 faults. The faulting system corresponds with the geology of the Niger Delta. From the generated structural surface map of Reservoir 2, Fault F7 at the flank of the crest forms an antithetic fault type with both F7A and F7B. This also aligns with the mundane trapping system of the study area. It is recommended that more wells should be drilled at strategic locations to provide more data that will contribute to quality reservoir models.

The study aims to integrate very low frequency electromagnetic method (VLF-EM) and vertical electrical sounding (VES) electrical resistivity methods to determine groundwater prospective in Ilara-Mokin, Akure. VLF profiling was carried out on eight traverses. VLF-EM profiling result showed areas which are relatively conductive with depth and VES stations were positioned based on the results of the VLF-EM survey. Eighteen VES were stationed with maximum electrode separation of 65m along six traverses trending East-West. A total of four geo-electric sections were generated in the N-S, WE , NE-SW and NW-SE directions revealing at most four geologic layers. The topsoil, clayey/lateritic layer, partially weathered to highly weathered layer and fresh bedrock have resistivity ranging from 105Ωm-445Ωm and a thickness of 0.5m-1.7m, 43Ωm-46Ωm and a thickness of about 6m, 200Ωm-811Ωm and a thickness of 0.5m-21.1m and 1122Ωm-6277Ωm respectively. The H, A, HA and AK curve types in the area revealed that the bedrock in the area is quite close to the surface. Also, the area is resistive as evident with the dominance of A curve type. VES points with H and HA curve types are likely groundwater prospects making the groundwater potential in the area to be rated as fair.

This study focuses on the use of some geostatistical tools to spatially distribute reservoir parameters in order to identify the bypassed prospects from the earlier seismic interpretation that was carried out in the field using 3D seismic data. Four wells and seismic data were used to generate the interpreted input horizon grids, fault polygons and to carry out detailed petrophysical analysis. Structural and property modeling which include; facies, net to gross, porosity and water saturation were distributed stochastically within the constructed 3D grid using Sequential Gaussian Simulation (SGS) algorithm. The reservoir structural model show system of different oriented growth faults F1 to F9. Faults F1, F2, F3 and F4 were the major growth faults, dipping towards south-west and are quite extensive almost across all the seismic section. A rollover anticline formed as a result of deformation of the sediments deposited on the downthrown block of fault F1. The other faults were minor fault (synthetic and antithetic). The trapping mechanism is a fault assisted anticlinal closure. Results from well log analysis and petrophysical models shows Godwin reservoir to be a moderate to good reservoir in terms of facies, with good net to gross, porosity, permeability and low water saturation. This study has also demonstrated the effectiveness of 3D geostatical modeling technique as a tool for better understanding the distribution with respect to space of continuous reservoir properties. It will also provide a framework for the future prediction of reservoir qualities and yield rate of the reservoirs.

Traditionally, sonic and density logs are vital components during the generation of synthetic seismogram. However, sonic logs as observed in many studies, often have poor quality or even absent in some cases. This work is a case study for the transformation of resistivity logs to pseudo sonic logs for the generation of pseudo synthetic seismogram considering the effect of gas. This research studies the relationship between resistivity and sonic logs in order to utilize the former for the generation of pseudo synthetics when sonic log is absent or poor. Standard synthetic seismograms were first created conventionally using sonic and density logs as inputs. The sonic log values were then plotted against the corresponding resistivity values for each well to derive their relationship using both linear and polynomial functions. Generally, the crossplot shows a fair correlation but some scattered plots were observed. Further probe into these observed anomalies revealed the areas to be gas saturated. A better correlation was achieved within affected zones by doing independent crossplots for previously gas delineated units. The standard synthetic generated were used as control for the pseudo synthetics and better correlation is observed when compared with the previous pseudo synthetics that does not acknowledge gas-effect.

This research aims at characterizing and modeling delineated reservoirs in ‘Falad’ Field, Niger Delta, Nigeria, to mitigate the challenge caused by the heterogeneous nature of the reservoirs. Seismic and well log data were integrated, and geostatistics was applied to describe the reservoir properties of the interwell spaces within the study area. Four reservoirs, namely RES 1, RES 2, RES 3 and RES 4, were delineated and correlated across four wells. The reservoir properties {lithology, net to gross, porosity, permeability, water saturation} of all the delineated reservoirs mapped were determined, and two reservoirs with the best quality were picked for further analysis (surface generation and modeling) after ranking the reservoirs based on their quality. Structural interpretation of the field was carried, nine faults were mapped (F1—F9), and the fault polygon was generated. The structural model showed the area is structurally controlled with two of the major faults mapped (F1 and F3) oriented in the SW–NE direction while the other one (F4) is oriented in the NW–SE direction. A 3D grid was constructed using the surfaces of the delineated reservoirs and the reservoir properties were distributed stochastically using simple krigging method with sequential Gaussian simulation, sequential indicator simulation and Gaussian random function simulation algorithms. Geostatistical modeling used in this study has been able to give subsurface information in the areas deficient of well data as the estimated reservoir properties gotten from existing wells have been spatially distributed in the study area and will thus aid future field development while also they are used in identifying new prospect by combining property models with structural maps of the area.