Application of Combined Analytical and Numerical Models for Water Production Diagnosis in Oil Wells

Abstract

Water production is inevitable in oil and gas fields, regardless of the field's
viability. Since water production is a big concern associated with oil and gas
production, properly identifying its source is paramount, as this will aid in
applying remedial techniques suitable to address it. Without proper diagnosis, a
cost increase in treatment, handling and management of this water results.
Furthermore, production will be shut down at its early stage, which is not a wise
decision. This problem can be curtailed if identified early by applying the
necessary remedial techniques. Due to these issues, the comparative investigation
into the complex dynamics of water production in oil reservoirs leads to the
application of combined Analytical and Numerical models to diagnose the water
production problems. The applied models were validated against real reservoir
data from 3 wells. The robustness and accuracy of these models were confirmed as
a result of positive outcomes from the diagnosed wells. Water production problems
were experienced in all case studies. Water production problems arising from the
flow through the channel were diagnosed by applying the Piecewise linear model,
early coning with late channeling was diagnosed using the hybrid model, and
coning was diagnosed using the exponential growth model. These analytical models
were used to determine the water breakthrough time for each well experiencing
water production problem, while Meyer, Gardner & Pison Method was used for
Critical Coning rate determination for well experiencing coning. Eclipse
Simulation software, the Numerical Model, simulates the water production
process, giving more detailed information about the mechanism. These findings
were validated against observed data and goodness-of-fit metrics, from which
excellent results indicated that the models explain 80% to 100% of the wells'
behaviours. From the findings, the petroleum industry has been equipped with
predictive tools to optimise reservoir performance, making this work stand at the
forefront of reservoir and production engineering, offering innovative solutions to
longstanding challenges.