Integration Geological Understanding With Geophysical Techniques for Better Reservoir Characterization – A Case Study in Ravva Block
Ravva Block is one of the most prolific hydrocarbon area in the Krishna Godavari Basin, on the eastern coast of India. The main reason for this is the location of the block which acted as the depo-centre for thick Miocene sediments. The depositional environment for these sediments vary from shoreface to deep marine setting driven by the fluctuation in the sea level. The Middle Miocene (MM) sands are the main reservoirs with an exploration, development and production history of nearly three decades in this block. The MM interval consists of excellent quality shoreface and distributary channel sands. Multiple local and regional unconformities along with listric and antithetic faults in the growth fault regime create excellent strati-structural hydrocarbon traps but at the same time brings in complexity within these reservoirs. With more than 80 wells, multiple 3D seismic and a huge wealth of production data there are still some unresolved questions especially with regards to the reservoir characterization and connectivity. This opens an opportunity to identify potentially un-swept and disconnected reservoirs and exploit them to arrest the production decline. The workflow adopted for this study is the integration of geological concepts including core and well data with different seismic attributes like spectral decomposition and inversion and then using the pressure data to complete the understanding. With good quality seismic data and the concepts of sequence stratigraphy used extensively at each stage the workflow can be broadly divided into four stages. First, the well log data are used to derive 1d depositional model, the same is then calibrated with the core sedimentology and environment of deposition. Second, the complex well correlation across the MM sequence is done and then validated with pressure data. Third, the horizons, unconformities and faults are picked in seismic and tied to the well markers and lastly the various seismic attributes are used to derive the sand fairways. The fairways are then back validated with the well information. This study improves the reservoir distribution and characterization understanding and are being immensely used in reservoir modelling, infill well placement and understanding areas devoid of wells with more certainty.
AAPG Datapages/Search and Discovery Article #90332 © 2018 AAPG International Conference and Exhibition, Cape Town, South Africa, November 4-11, 2018