IJInn 2017 Volume 7 Issue 4

International Journal of Innovation (IJInn) ISSN:0975 – 9808

An Open Access Journal -- NO Fees -- NO Processing Charges -- 100% Non Profit Initiatives

Characterisation of Hydrocarbon Reservoirs in Bonny area of Niger-Delta, using Probabilistic approach. K.C. Onuigbo and Prof. M.U. Igboekwe. IJINN (2017), 7(4):22-33




Characterisation of Hydrocarbon Reservoirs in Bonny area of Niger-Delta, using Probabilistic approach

Authors & Affiliation:

K.C. Onuigbo and Prof. M.U. Igboekwe

Department of Physics (Geophysics), College of Physical and Applied Sciences, Michael Okpara University of Agriculture, Umudike, P.M.B 7267 Umuahia, Abia-State, NIGERIA

kenethonuigbo@yahoo.co.uk, igboekwemu@yahoo.com


This work proposed a joint estimation of petro-physical properties which combines statistical rock physics and Bayesian seismic formulation. This work is to present a strategy for estimating the probability distributions of petro-physical parameters and litho-fluid classes from seismic. The estimation of the hydrocarbon reservoir properties and the associated uncertainty is performed in three steps: firstly, a rock physics model is established using well log data and seismic data to predict elastic attributes (velocities or impedances) from petro-physical properties, after which an elastic property from partially stacked seismic angle gather is estimated. Finally, the conditional probability of petro-physical variables and litho-fluid classes is calculated. The application of this reservoir study included two well data (well A and well B) and partially stacked seismic volume which provided the probability density of petro-physical properties and litho-fluid classes. This clearly demonstrates the applicability of the proposed statistical method. Results obtained showed that well A had effective porosity between 40% - 55%, clay content 34cm3 – 48cm3 and water saturation between 10cm3 – 20cm3 and well B had effective porosity between 20% - 25%, clay content between 54cm3 – 60cm3 and water saturation between 25cm3 – 40cm3. Due to this result, well A will have greater production that would last for years at a true vertical depth (TVD) of between 5720ft – 5855ft. It is therefore concluded that probabilistic method of estimating hydrocarbon reservoir works better in the near surface layer of the overburden, where the signal to noise ratio is high , rather than the lower layer where the signal to noise ratio is low.

Keywords: statistical rock physics, Bayesian seismic formulation, stacked seismic volume, effective porosity, clay content, water saturation, hydrocarbon reservoirs