Improving Reservoir Facies Model by Successful Application of Forward Stratigraphic Modeling Techniques for Offshore Deltaic Reservoir in India
Authors: Moharana Abhishek , Mahapatra Mahabir Prasad , Chakraborty Subrata Kumar , Biswal Debakanta , Havelia Khushboo 
Published: November 2019

Petroleum Geologists have always been a group who looked at rocks, developed and described depositional concepts, mapping structures to discover and develop hydrocarbons for profit. With the advent of new technologies and computing power, geology started to become a lot more quantitative. The first wave of this new revolution was the introduction of geostatistics and the discipline of geomodelling, dealing with quantitative statistics like variograms, histograms, stochastic models which could be used to put a number and range on the geological uncertainty. However, geostatistics which was originally developed in the mining industry in the 1950's deals more with regularly sampled data, describing their spatial variability and directionality. In majority of development fields, with many wells sampling the reservoir, geostatistics helps us to create a feasible proxy for the subsurface reservoirs, when it is backed by a strong conceptual geological foundation. However, as the number of wells decreases, the data for geostatistical analysis reduces and a geomodeller must rely strongly on the conceptual geological knowledge, to build a predictive geological model rather than the noisy picture which over-reliance on blind geostatistics can provide. Until recently, there was no way of quantifying or visualizing depositional concepts in 3D for a geologist save for few block diagrams and average sand distribution maps. However, these were mostly manual, deterministic with a long turnaround time for any alternate concepts.

A relatively recent and still underused addition to the geologist's set of quantitative tools has been geologic process modeling (or GPM, also called stratigraphic forward modeling). This technique aims to model the processes of erosion, transport and deposition of clastic sediments, as well as carbonate growth and redistribution on the basis of quantitative deterministic physical principles (Cross 1990; Tetzlaff & Priddy 2001; Merriam & Davis 2001). The results show the geometry and composition of the stratigraphic sequence as a consequence of sea-level change, paleogeography, paleoclimate, tectonics and variation in sediment input. In its scope, GPM is similar to detailed sequence stratigraphy. However, the latter has been developed on the basis of observations and inferences, mostly from seismic data, and conceptual models that specify what stratigraphic relationships should be expected under certain conditions (such as sea-level rise and fall, or variations in sediment input). GPM on the other hand, is based solely on numeric modeling of open-channel flow, currents, waves, and the movement of sediment. The observed stratigraphy is the result of modeling a physical system which can then be further used for refinement in a geological facies model. (Tetzlaff et. al 2014)

In the currents study a 3D geological model for the B-9 field, based on the Geological Process Modeling (GPM) has been attempted Owing to the thin pays in deltaic sands, understanding reservoir continuity from seismic data was not possible. With only 4 wells available in the field, traditional geostatistics based facies models were inadequate in explaining the reservoir distribution. Thus, a combination of Stratigraphic Forward Modeling with Multi Point Statistics is used to accurately capture sub-surface facies heterogeneity.