Abstract

Bombay High is the largest oil field discovered in India so far. Major hydrocarbon accumulation is in the middle and lower Miocene layered carbonates with shale intercalations. Many wells of the field have become sick due to high water cut, high GOR and rapid pressure decline. To understand the present scenario, reservoir characterization of a selected area was carried out by integrating petrophysical, geological, reservoir and seismic data. From the reinterpretation of the available seismic data, subtle faults could be identified. Detailed facies analysis has been carried out, with the innovative concept of generation of facies ratio maps using core and well log data as inputs. Using statistical multiple regression analysis, core and well log data were combined and a permeability relationship has been derived to generate a permeability log in each well. Permeability was successfully scaled up to the reservoir level by matching the log derived permeability to the well test permeability. Reservoir quality had been estimated combining the permeability data with facies analysis. RFT pressure depletion analysis has been carried out to examine the effectiveness of intervening shales as flow barriers. Resistivity modeling was used to understand the formation true resistivity character and to examine the side bed effects, in this layered sequence.

The identified faults can have considerable impact on the fluid contacts. Facies analysis has given proper insight into the depositional environment. Permeability estimation has led to better visualization of the fluid flow behavior both laterally and vertically across the study area. RFT pressure data analysis, along with the facies analysis could identify the hydraulic sealing character of various shale layers. Resistivity modeling showed that a significant increase in the net hydrocarbon pore volume can be achieved by carrying out judicious corrections on the measured resistivity, especially with the induction type measurements.

Generation of detailed facies ratio maps, study of spatial variations in permeability, usage of resistivity modeling for understanding the formation true resistivity character and such other discussed techniques can be applied to characterize similar complex carbonate reservoirs.

Introduction

Bombay High field is situated 160 Km WNW of Bombay city in Bombay High uplift area in the Arabian Sea (Fig 1). It is the biggest oil field discovered in India so far. The structure is an asymmetric doubly plunging anticline. An EW fault divides the Bombay High structure into North and South sectors. A major fault limits the field on the East and an aquifer on the West. Major portion of oil reserves is in Middle and Lower Miocene carbonate sediments. The main pay section, called L-III reservoir, comprises several limestone layers with intervening shales. The limestone layers have the nomenclature: A1, A2-I, A2-II, A2-III, A2-IV, A2-V, A2-VI, A2-VII, B, C and D. They are separated by M, M1, M2, F-41, M3, M4, M5, N, O and P shales respectively (Fig 2). The limestone layers are heterogeneous in character with considerable spatial variation in their reservoir properties. The degree of vertical communication of the intervening shales is also varying. Oil production from the South sector started in March 1980 and water injection started in 1987.

Many wells in this field have become sick, because of high water cut, high GOR, decline in reservoir pressure and with large number of layers open to production as well as water injection. A selected area of the South field was taken up to understand the present production scenario. The area of study is in the northern part of Bombay High South field consisting of two rows of platforms (Fig. 1). The area is bounded on North by the E-W fault separating South and North Bombay High fields, on East by a N-S fault, on the west by the oil water contact and on the south the area is open. The study area consists of nineteen platforms having 119 development wells and several exploratory wells.

From the reinterpretation of the available seismic data, subtle faults could be identified which can have considerable impact on the fluid contacts. The facies ratio maps generated, using core and well log data as inputs, have given proper insight into the depositional environment, especially the shale characteristics. Core and well log data have been combined to derive a permeability relationship using multiple regression techniques to generate a continuous permeability log. A relationship between log derived permeability and the well test permeability was derived for mapping the permeability across the study area and visualize the fluid flow behaviour. Reservoir quality was estimated combining the permeability data with facies analysis. Analysis of RFT pressure data along with the facies analysis could identify the hydraulic sealing character of various shale layers.

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