Abstract
A deepwater turbidite formation from Eastern Offshore, India, is a major focus for hydrocarbon exploration. The reservoirs in this field are primarily of low resistivity and low contrast and consist of thinly laminated shale-sand laminae with overlying thick shales. Conventional logs do not sufficiently distinguish between the overlying shales against the laminated reservoir intervals- owing to poor vertical resolution of the tools to characterize the thin beds properties. A standard practice followed by the operating company was acquisition of conventional logging data along with tensor resistivity measurement for a laminated-shaly sand analysis (LSSA) followed by formation testing. While multiple new pay sands were discovered through this method, the sand-shale-fluid model of LSSA is insufficient to provide fluid typing. Furthermore, fluid sampling using formation testers in these unconsolidated formations are risky due to relatively high SOBM invasion and therefore high clean-up time is required to collect samples. Due to the similar properties between the SOBM and formation oil, it is difficult to conclude between the two fluids during real-time monitoring. Thus, it was essential to delineate the formation fluid using methods other than formation testing.
The acquisition of magnetic resonance data and an integrated interpretation involving conventional logging, tensor resistivity and NMR data helped overcome these challenges, prior to formation testing. The electrical anisotropy and borehole image data helped identify thin beds. LSSA outputs based on conventional and tensor resistivity data indicated hydrocarbon bearing intervals. A continuous magnetic resonance measurement acquiring the longitudinal relaxation (T1), transverse relaxation (T2) and the diffusion coefficient (D), helped derive a lithology independent fluid typing in these wells to provide insights before formation testing.
Hydrocarbon bearing sands were identified as per the results of the integrated analysis, and the formation testing intervals were optimized. Conventional resistivity inversion, LSSA saturation and flushed zone saturation from magnetic resonance provided an understanding of the invasion. The hydrocarbon bearing intervals delineated from integrated formation evaluation using LSSA and 2D NMR analysis were successfully tested and proven using formation testing and sampling. Subsequently, the exploratory well logging programs were modified to include the magnetic resonance in future wells and the workflow explained herein was adopted field-wide.
This paper provides a framework for integrated data interpretation using multi-component induction, magnetic resonance, acoustic data and resistivity imager logs to quantify reservoir fluids and subsequently provide an alternative to formation testing and provides a workflow for exploratory wells for Eastern Offshore, India.
