Integrated Approach of Reservoir Characterization Using Multi-Component Induction Tool in Thinly Laminated Pay Sands- A Case Study from Eastern Offshore India

Abstract

Abstract A number of exploratory wells were drilled in Eastern Offshore of India, encountering thick turbiditic sequences. The formation evaluation through conventional logging tools is a challenge in such depositional environments as the tools are unable to resolve thin beds and provides a weighted average log response over a collection of beds. In such environments, often the potential pay intervals are overlooked if comprehensive petrophysical analysis is not carried out. While the thin bed problem underestimates the reservoir potential, the orientation of measurement of the petrophysical properties further complicates the problem due to formation anisotropy. Another important characteristic of layered thin bed sand shale sequence is the acoustic anisotropy due to the transversely isotropic nature of sedimentary deposition. The multicomponent induction tool was logged in the study area, providing a tensor measurement of the horizontal (Rh) and vertical (Rv) components of resistivity. The well encountered thick turbidite sequence of laminated pay sands with very low resistivity contrast. The initial stochastic petrophysical analysis from conventional open hole log responses indicated poor reservoir quality with high water saturation. Integration of high-resolution acoustic data and VTI analysis with multicomponent induction tool shows a clear evidence of alternating shale and sand sequences in the target reservoir. A high-resolution processed acoustic porosity was incorporated to build the lithology model with multicomponent resistivity data. Integration of ResH, ResV and VTI into a Thomas-Stieber petrophysical model indicates potential hydrocarbon bearing sands at two depths which were further included to optimise the formation testing and sampling plan. During fluid sampling at the two identified depths, 54 and 157 ltrs. of fluid volume was pumped out before collecting samples by utilizing real time downhole fluid identification technologies. Optical absorbance and refractive indices were used to differentiate between miscible fluids. Clean-up from SOBM to formation oil was monitored using trends in representative channels of constantly changing absorbance spectrum. The formation testing results, therefore, were in good agreement with the identified pay intervals from the T-S model. Furthermore, Stoneley permeability analysis were carried out in the study area and calibrated with formation testing results. In the absence of imager data in the example well, formation dip was computed based on the multicomponent induction tool, which provided a close match to the OBM imagers, which struggled due to low formation resistivity, logged in adjacent wells. This paper highlights the integrated workflow of multicomponent resistivity data based Thomas Stieber petrophysical model with high resolution acoustic and formation tester results of the example well and its success in delineation of pay sand intervals.