Hydrocarbon Reservoir Characterization Using Multi-point Stochastic Inversion Technique: A Case Study of Pennay Field
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Original Paper
Hydrocarbon Reservoir Characterization Using Multi-point Stochastic Inversion Technique: A Case Study of Pennay Field Akindeji O. Fajana1,2 Received 5 August 2020; accepted 29 September 2020
Various limitations mitigate our understanding of the intrinsic properties of subsurface formations during reservoir characterization. These challenges go beyond data set discrepancies, but the various analytical methods, workflow data reconciliation patterns, and scale disparities all affect the final outlook to be inadequate. A multi-point stochastic inversion technique was applied to characterize the three-dimensional seismic and a collection of Pennay Field borehole logs, Niger Delta, outside of well control. The characterization involved the structural interpretation of four horizons, namely the horizons 1–4. The identification of potential hydrocarbon zones involved identification of hydrocarbon-bearing sands, correlation of identified sands across wells, determination of petrophysical properties of identified hydrocarbon-bearing sand, and the integration of well information from seismic data. Potential hydrocarbon zones have been delineated, and the petrophysical properties have been predicted away from well control using the seismic volume data. The net-to-gross and net thicknesses in millisecond were computed over the interval and defined in terms of minimum, maximum, mean, standard deviation, and percentiles P1O, P25, P50, P75, and P90. The 90% net-to-gross values are above 0.6, while the 75% net-to-gross values are between 0.35 and 0.99 in most areas. Moreover, the 50% net-to-gross values range between 0.35 and 0.85 while 25% and 10% net-to-gross values are below 0.4 in most areas in the studied field. Attention should be given to regions with structural closure, higher net-togross, and subsequently higher net thickness, low volume of shale, low gamma-ray, low water saturation, and higher connectivity as predicted from the structural, petrophysics, stochastic, and cross-plot analyses for further exploration and exploitation activities. KEY WORDS: Reservoir, Stochastic, Hydrocarbon, Percentiles, Petrophysics.
INTRODUCTION Exploration methods based on geophysical concepts have been used repeatedly in the last century to investigate the energy resources and raw 1
Department of Geophysics, Federal University Oye, Ekiti State, Oye, Nigeria. 2 To whom correspondence should be addressed; e-mail: [email protected]
materials required by modern civilization. The growing population has continually increased the pressure on the available natural resources, thus placing an increased demand on other elements of civilization. This demand has created new geophysical tasks relating to the need for detailed knowledge technically for hydrocarbon exploration, recovery, and development purposes. The most targets of exploration exercises are geological, geophysical,
Ó 2020 International Association for Mathematical Geosciences
A. O. Fajana environmental, and engineering interest both at shallow depth, ofte
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