Computation of High Resolution Variable ‘m’ for Heterogeneous Reefal Carbonate System; A Case Study from Western Offshore India
Giant carbonate fields in the Mumbai off shore are expected to be the dominant source of hydrocarbon production in the country. Hence, understanding carbonate reservoirs and producing them efficiently have become industry priorities. The D1 structure of Mumbai block is NW-SE trending doubly plunging anticline along edge of Paleogene Shelf slope break, located at a distance of 200 km of Mumbai coast. From production point of view, middle pay & upper pay of this structure have been established as proven reservoir. However, lower pay with all its potential reservoir quality is yet to be assessed. In order to assess a possible hydrocarbon reservoir, hydrocarbon saturation needs to be determined with good accuracy. In 1942 Archie published a formula to estimate water saturation in reservoirs. In case of carbonates, the saturation computed by the formula is not always correct. The factors complicating the role of the formula are known as porosity exponent (m, also known as cementation factor) and saturation exponent (n). Both exponents tend to vary quite often in the carbonate reservoirs. With the exception of cores, no reliable and well established techniques exist today that can give a good estimate of these exponents. In particular with reefal carbonates where the extent of vertical heterogeneity and spatial distribution is enormous; this conventional assumption of constant values for cementation exponent (m) does not exhibit the true picture of saturation. Hence, estimating ‘m’ from the well log is the main objective of this paper. The technique addressed in it is based on the assumption that the amount and pattern of cementation, caused by diagenesis, in carbonates is one of the factors controlling the value of ‘m’. Therefore in order to estimate it for carbonates, the cementation in them should be quantified. It was achieved through integration of electrical borehole images and petrophysical logs with the core. The present study aimed at improving the saturation computation using variable ‘m’ values obtained from characterizing the vertical and lateral textural details on high resolution microresistivity image & taking into consideration the type of lithology, compaction effect and the presences of secondary features like vug & fractures etc. This study also aims at the characterization of each individual 9 sub pays which are identified in Lower Pay of D1 structure of DCS Field considering all available static and dynamic data set.
AAPG Datapages/Search and Discovery Article #90194 © 2014 International Conference & Exhibition, Istanbul, Turkey, September 14-17, 2014