Predicting Carbonates through Time and Space: Deep Time Climate Modeling and Interactive Databases identifying Heterogeneity, Morphometrics and Reservoir Quality
Despite the notion that carbonates are holding more than 60% of undiscovered reserves, global exploration results over the last decade have dampened expectations. One reason is uncertainties around seismic identification, which have not come down. Another the cost of development and characterization of carbonate reservoirs, which is still more expensive and challenging than sandstone reservoirs. Several joined industry-academic research projects are aiming to reduce uncertainty in exploration and optimize reservoir characterization. Deep time paleoclimate modeling is to deliver probabilistic maps of carbonate presence through time and space with special emphasis on the Eocene to Miocene carbonates in Southeast Asia and calibrated to present TOTAL prospects and operated fields. In addition to risk reduction, those may assist in identification of frontier basins and play type development. Another project is to better constrain geological control (e.g., texture, environment of deposition, diagenetic modification, and heterogeneity) on multi-scale reservoir quality, in other words, to improve the risking of effective reservoir presence. An early (Aptian) pilot demonstrated that current deep time paleoclimate modeling workflows (modified ISPL models) and paleogeographic reconstructions (modified Scotese models with shoreline and shelf break positions constraining ‘’shallow carbonate’’ bathymetry) are sufficiently robust to test concept and distribution of “carbonate factories” (associations of grain types that share a common set of ecological behaviors). In particular, the abundance and quality of information and relevant knowledge in the Eocene to Miocene interval makes this period an excellent starting point for estimating the probability of occurrence in space and time, hence the interest in Southeast Asia. In parallel, several relational databases provide and supplement the geological and environmental information underpinning the paleoclimate simulations. Once of those databases provides morphometric properties (i.e., shape, dimensions, juxtaposition) and geological attributes and, hence, determines contrast-comparison with typical probabilistic distributions of carbonate systems and elements to reduce uncertainty. To identify which geological attributes have common relevance (influence the distribution – heterogeneity – of multi-scale petrophysical properties), an exhaustive capture of the public domain, commercial databases and in-house data resulted in core - to well-scale characterization. More than 200 in-house carbonate reservoir zones (from more than 20 field scale static and dynamic models) were screened to supplement reservoir-scale property ranges. The resulting relational database allows for quick screening, across core to reservoir scale and a number of geological attributes (i.e., depositional texture, grain types, primary and secondary porosity) probabilistic (P10-P50-P90) distributions of, i.e., porosity, permeability and NTG. In addition, it facilitates estimation of the relative contribution of diagenetic modification (of depositional texture) to flow and therefore the heterogeneity of the prospect or reservoir. Both, multi-year, projects, will deliver important alternative workflows toward reducing uncertainty in the identification and risking of carbonate presence and reservoir quality in prospects and optimize the integration of relevant geological information in carbonate reservoir characterization.
AAPG Datapages/Search and Discovery Article #90371 © 2020 AAPG Asia Pacific Region, The 1st AAPG/EAGE PNG Geosciences Conference, PNG’s Oil and Gas Industry: Maturing Through Exploration and Production, Port Moresby, Papua New Guinea, February 25-27, 2020