Time-Lapse Pulsed Neutron Logging Helps Maximize Recoveries from Mature Field - Case Study from Mangala Field of Rajasthan, India

Mangala Oilfield of Rajasthan has produced over 36% of STOIIP and has been subjected to several innovative and new era technologies since it started producing in August’ 2009. Initially, field was under Water flood phase till April’2015 and then full field Polymer flood phase started to maximize recovery. Mangala field with medium-gravity viscous crude oil & formation water salinity of approximately 8000ppm has an excellent reservoir property of high porosity (24 to 26%), high permeability (200md- 20D) and very low irreducible saturation i.e., less than 5%. Thus, C/O logging in this field has been a very good choice to estimate the remaining oil saturation (ROS) and understand the sweep of oil due to injection which in turn has helped in maximizing recoveries from the field. Time-lapse PNL were run in several wells to monitor the efficacy of the water flood/polymer flood phase on oil recovery. The objective was two-fold; to estimate the change in saturation over time and to identify by-passed or marginally swept intervals. The process begins with recording the initial saturation in the wells before any production has occurred. Then time-lapse data are recorded to monitor the change in saturations. Secondly, saturation estimation from PNL data were used to plan the next course of action- workover operations, changing completion zones, abandoning certain zones or wells, and infill drillings. PNL data in combination with other reservoir surveillance techniques (MPLT) has proved to be a vital surveillance tool to maximize the recovery from this field. In this paper, we present the effectiveness of PNL tool specially RMT-I with production data over a period of 3 years (post Aug 2019). However, the results also include integration of other PNL dataset (RST & Raptor) acquired for reservoir surveillance activity and the challenges involved in interpreting the result of different PNL tool over time. In absence of RMT 3D tool, PNL is acquired as 1 Sigma up/down pass and 3 CO up passes at 1fpm-3fpm to address the uncertainty related to gas presence on C/O interpretation. Sigma measurement helped in identifying gas below packer or in the annulus behind pipe and helped in addressing the uncertainty related to gas presence on C/O interpretation. Secondly, RMT was planned in infill well post drill to determine the uncertainty between OH and Cased hole Oil saturation. The results agreed with production data and uncertainty in oil saturation estimation was minimized to 10-15% approximately. Several cases will be discussed in the paper to demonstrate the use of PNL logs for reservoir management.