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Mangala Polymer Flood Performance: Connecting the Dots Through In-Situ Polymer Sampling

Authors: Vivek Shankar; Sunit Shekhar; Abhishek Kumar Gupta; Alasdair Brown; Santhosh Veerbhadrappa; Petro Nakutnyy;

Mangala Polymer Flood Performance: Connecting the Dots Through In-Situ Polymer Sampling

Abstract

Summary The Mangala field contains medium-gravity viscous crude oil. Notably, it is the largest polymer flood in India and 34% of the stock tank oil initially in place (STOIIP) has been produced in 11 years. Mangala was put on full field polymer flood in 2015, 6 years after the start of field production on waterflood in 2009. Polymer flood added nearly 93 million barrels above the anticipated waterflood recovery in 6 years. Reservoir simulation models could replicate the initial Mangala polymer flood performance. However, the performance of the lower layers of Mangala (FM-3 and FM-4) continued to progressively deviate from modeling estimates. Importantly, the observed polymer breakthrough deviated significantly from predictions. As the polymer flood matured, the trend of field water cut with time indicated that in-situ polymer viscosity was equivalent to only 50 to 60% of the surface polymer viscosity. For better predictions and corrective actions, it was necessary to understand the nature of degradation, the progressively deteriorating field performance, especially of the lower layers, and the deviation of polymer breakthrough trends from predictions. Carefully designed in-situ polymer sampling, laboratory studies, and reservoir modeling studies helped connect the dots to understand the field performance. There are several excellent publications on accelerated aging studies and some on polymer sampling. This paper offers an opportunity to directly compare experimental results with field data. The procedures used and lessons learned during field sampling can be useful for other operators for management of polymer floods.

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
7
Top 10%
Average
Top 10%