Implementation of an Exploration Workflow to Characterize a Low Poro-Perm Gas-Bearing Prospect Using Rock Physics Depth Trends to Assist Avo Classification

Abstract

An Oil and Gas company is not able to sustain over the time without creating value through its life cycle. In the last decades PetroSA has been using sophisticated seismic and geological survey techniques to determine whether viable oil and gas reservoirs may exist and identify potential well locations for exploration drilling by performing independent play fairway analysis to evaluate the potential of the Syn-Rift II Valanginian Upper Shallow Marine (USM) formation. The prospect of interest is defined as a gas-bearing Upper Shallow Marine (USM) sands and is one of the most attractive prospects documented in the Bredasdorp basin, south coast South Africa in term of geological risk and potential volumes. One of main risks are associated to reservoir presence and quality. A single well was drilled in the area of interest but planned to target a shallow reservoir. On the other hand, few wells that targeted the same formation at a similar depth level are located far away from the interest structure. This paper describes a methodology which attends to de-risk this prospect in the USM by calculating the AVO response as a function of litho-pore fluid facies by using rock physics depth-trend. Data from analogue wells and/or nearby areas are used to determine the distribution of Vp, Vs and density for each likely facie defined and empirical porosity-depth trend models are computed to calibrate such data to the given depth of interest. The different facies defined above are then combined to each other to cover all the realistic interface scenarios on the geological setting of interest. The interfaces AVO responses are computed using an approximation to the AVO Zoeppritz equation (Shuey), and AVO pdfs are then calculated from each interface scatter plot to predict the most likely litho-pore fluid facies from seismic (I,G) attributes. The top of reservoir interface resulted classified as an AVO “Class I” characterized by a high zero-offset amplitude. The AVO response showed a good separation between litho-facies (sand-shale), but more subtle between fluid cases (sand-gas, sand-water) in the AVO attributes (I,G) domain. On the other hand, the main driver for an efficient AVO classification in this low poro-perm reservoir is controlled by the porosity, so an overlapping between interface clusters in the A-B domain was noticed.

AAPG Datapages/Search and Discovery Article #90332 © 2018 AAPG International Conference and Exhibition, Cape Town, South Africa, November 4-11, 2018