The Cambay Basin in western onshore India has been on production for a long time and most of the easy-to-find reservoir facies are being exploited by different operators. However, the complex setting of the basin provides opportunity for exploration of many other reservoir facies distributed throughout the basin. Tarapur field is located in a relatively lesser understood part of the basin and understanding the distribution pattern of prospective reservoir facies in this field has been a challenge for optimal exploitation of this area.

An integrated approach has been developed to understand the complexity of the reservoir in a sequence stratigraphic framework integrating the geosciences data from different domains. Borehole images, conventional openhole log data, mud log, nuclear magnetic resonance and background geological information have been incorporated and integrated with seismic backdrop to understand the signatures of geological agencies on the formation across different scales which govern the distribution and geometries of the facies.

Different lithofacies were identified with the help of master log and conventional open hole logs, incorporating the finer textural details from borehole images. The artificial neural network methodology helped in properly differentiating the sub-facies and provided a firm basis for extrapolating the facies associations across different wells of the field. The association of these lithofacies and their orientation derived from the dip data revealed the possible assemblages of depositional sub-environments encountered in a single well. Facies assemblages are mainly comprised of silt, shale and coal lithofacies. These are vertically distributed with a specific fining and coarsening upward trends which are in turn inferred in terms of depositional sub-environments. The study reveals different stages of sediment build up and their vertical facies stacking pattern leads to the identification of two parasequences. By extrapolating the interpreted facies model honoring the petrophysical properties in nearby wells, a good control on the conceptual geological model is achieved. Based on facies association analysis, marginal marine sedimentary environment is envisaged. The stacking pattern of facies associations is interpreted in terms of prograding parasequences which are also identified in seismic line validating the conceived depositional model. This sequence stratigraphic framework provides the predictive value to the model for reservoir facies distribution.

Being the first of its kind in the field, this study provides a methodology that aids in the optimization of exploration strategy. The high resolution seismic attribute analysis coupled with the conceptual model would help in locating the new exploration leads.

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