UKH Journal of Science and Engineering | Volume 5 • Number 1 • 2021 119
Comparison Between Homogenous and Heterogeneous
Reservoirs: A Parametric Study of Water Coning Phenomena
Frzan F. Ali
1, a
, Maha R. Hamoudi
2,b*
, Akram H. Abdul Wahab
3,c
1
Department of Petroleum Engineering, College of Engineering, Knowledge University, Erbil, Iraq
2,3
Department of Natural Resources Engineering and Management, School of Science and Engineering, University of
Kurdistan Hewler, Erbil, Iraq
E-mail:
a
frzan.ali@knu.edu.iq,
b
m.hamoudi@ukh.edu.krd,
c
a.hamoodi@ulh.edu.krd.
1. Introduction
Water production is one of the most common phenomena during the exploitation of oil. Normal rise of oil water contact,
water coning, and/or water fingering are the reasons for such phenomena. This serious problem is quite common in
the Middle East where large oil reservoirs have water aquifers or active water drives underneath. When excess water
production exists, the costs associated to surface facilities, artificial lift systems, corrosion and scale problems increases.
Besides, the recovery factor decreases as oil is left behind in the displacement front. These factors reduce the economic
indicators. In order to optimize production, the drastic influence of water production must be soon detected, and the
Access this article online
Received on: March 11, 2021
Accepted on: April 19, 2021
Published on: June 30, 2021
DOI: 10.25079/ukhjse.v5n1y2021.pp119-131
E-ISSN: 2520-7792
Copyright © 2021 Frzan et al. This is an open access article with Creative Commons Attribution Non-Commercial No Derivatives License 4.0 (CC
BY-NC-ND 4.0)
Research Article
Abstract
Water coning is the biggest production problem mechanism in Middle East oil fields, especially in the Kurdistan
Region of Iraq. When water production starts to increase, the costs of operations increase. Water production from
the coning phenomena results in a reduction in recovery factor from the reservoir. Understanding the key factors
impacting this problem can lead to the implementation of efficient methods to prevent and mitigate water coning.
The rate of success of any method relies mainly on the ability to identify the mechanism causing the water coning.
This is because several reservoir parameters can affect water coning in both homogenous and heterogeneous
reservoirs. The objective of this research is to identify the parameters contributing to water coning in both
homogenous and heterogeneous reservoirs. A simulation model was created to demonstrate water coning in a single-
vertical well in a radial cross-section model in a commercial reservoir simulator. The sensitivity analysis was
conducted on a variety of properties separately for both homogenous and heterogeneous reservoirs. The results
were categorized by time to water breakthrough, oil production rate and water oil ratio. The results of the simulation
work led to a number of conclusions. Firstly, production rate, perforation interval thickness and perforation depth
are the most effective parameters on water coning. Secondly, time of water breakthrough is not an adequate indicator
on the economic performance of the well, as the water cut is also important. Thirdly, natural fractures have
significant contribution on water coning, which leads to less oil production at the end of production time when
compared to a conventional reservoir with similar properties.
Keywords: Water Coning, Homogeneous Reservoirs, Heterogeneous Reservoirs, Production
Optimization.
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source of such problems must be identified in order to apply effective and suitable techniques to control water
production (Gasbarri et al., 2007).
The cause of water coning is an imbalance between the viscous and gravitational forces around the completion interval.
In other words, the flow of oil from the reservoir to the well introduces an upward dynamic force upon the reservoir
fluids. This dynamic force is due to wellbore drawdown causes the water at the bottom of the oil later to rise to a certain
point at which the dynamic force is balanced, by the height of water beneath that point. Now as the lateral distance
from the wellbore increases, the pressure drawdown and the upward dynamic force decrease. Thus, the height of the
balance point decreases as the distance from the wellbore increase. Therefore, the locus of the balance point is a stable
cone shaped water oil interface. At this stable situation oil flows above the interface while water remains stationary
below the interface (Gasbarri et al., 2007).
This work addresses the water coning issues in a conventional and naturally fractured reservoir via a numerical
simulation approach on a single-well radial cross-section using commercial reservoir simulator (ECLIPSE 100).
Understanding the key parameters affecting water coning in both homogenous and heterogeneous reservoirs will lead
accurate identification of the problem and effective solution to mitigate or control the water production. This is an
effective production optimization approach for water producing reservoirs.
1.1. Coning Development
Producing oil from a well which is overlying water may cause the oil/water interface to deform into a bell shape. This
deformation is called water coning and occurs when the vertical component of the viscous force exceeds the net gravity
force (Hoyland et al., 1989). Therefore, two forces control the mechanism of water coning in oil and/or gas reservoirs:
dynamic viscous force and gravity force. Water coning phenomenon constitutes one of the most complex problems
pertaining to oil production (Saad et al., 1995). Coning phenomenon is more challenging in fractured reservoirs owing
to their heterogeneous and high permeable medium of the fractures compared to matrixes (Foroozesh et al., 2008). On
the other hand, water coning in naturally fractured reservoirs often result in excessive water production which can kill
a well or severely curtain its economics life due to water handling (Beattie & Roberts, 1996).
In the study of water coning phenomenon both in conventional and fractured reservoirs, three parameters are
determined: critical rate, breakthrough time and water cut performance after breakthrough. It is of essence to understand
the term critical rate. At a certain production rate, the water cone is stable with-it apex at a distance below the bottom
of the well, but an infinitesimal rate increase will cause instability and water breakthrough. This limiting rate is called the
critical rate for water coning (Hoyland et al., 1989). Therefore, critical rate is defined as the maximum allowable oil flow
rate that can be imposed on the well to avoid a cone breakthrough (Salavatov & Ghareeb, 2009).
In fractured reservoirs, critical rate is influenced by extra factors such as fracture storativity (ω), fracture transmissivity
(λ), fracture pattern and their interaction to matrixes; especially around the wellbore (Namani et al., 2007). Bahrami et
al. (2004) stated that because of heterogeneity and non-uniform fracture distribution in naturally fractured reservoirs,
the development of cone is asymmetrical, and estimation of critical rate and breakthrough time requires modelling with
an understanding of fracture pattern around the producing well.
These are the challenges of studying water in fractured reservoirs. In these reservoirs, the extent and stabilization of
cone growth depend on factors such as; oil zone thickness, mobility ratio, the extent of the well penetration and vertical
permeability; of which the most important parameter is the total production rate (Namani et al., 2007). Moreover, water
coning depends on the properties of the porous media, distance from the oil-water interface to the well, oil-water
viscosity ratio, production rate, densities of the fluids and capillary effects. Conversely, in fractured reservoirs this
problem is more complicated because of the dual porosity system in the fractured reservoir which results in formation
of two cones (i.e., coning in the fracture and matrix). Depending on the rates, a fast-moving cone may be developing in
the fracture whilst a slow-moving cone is observed in the matrix. The relative position of the two cones is rate sensitive
and is a function of reservoir properties (Al-Aflagh & Ershaghi, 1993). The key parameter in determining water coning
tendency is the vertical to horizontal permeability ratio, kv/kh. The existence of natural fractures however often results
in high values of kv/kh providing conditions conducive to water coning (Beattie & Roberts, 1996). Therefore, high
vertical permeability in fractures is bound to accelerate the coning process resulting in lowering of the critical rates and
more rapid breakthrough times. In addition, the favored path for fluid flow through the fractures and the uneven fracture
conductivities commonly observed in naturally fractured reservoirs is expected to affect wells regardless of their
structural position (Al-Aflagh & Ershaghi, 1993). Understanding the effect of various rock and fluid properties such as
UKH Journal of Science and Engineering | Volume 5 • Number 1 • 2021 121
oil thickness, absolute permeability, completion interval location, production rate, fluid viscosity and density is very
crucial (Foroozesh et al., 2008).
2. Methodology
Water coning in vertical wells is considered as one of the most complex problems facing any well during its production
life. In the past, water coning phenomena in naturally fractured reservoirs were studied using a homogenous model due
to its convenient use, ease of simulation of work, and cost. However, it is not very well understood which well/reservoir
parameter affects water coning in a conventional reservoir, and how different that relationship is to a naturally fractured
reservoir. Accurate results of water coning in a naturally fractured reservoir cannot be obtained if a homogenous model
is used in the simulation work.
In this research, the following work has been performed:
1- Create Conventional Model1 and Naturally Fractured Model1
2- Compare Conventional Model1 with Naturally Fractured Model1 in order to prove the quality and accuracy of
the simulation work. (Both models having the same reservoir and well properties, including similar porosity-
permeability of the fractured layer to the matrix layers in the naturally fractured model).
3- Modify Naturally Fractured Model1 to create the Base Case of a Naturally Fractured model. Unlike in the
previous case, a realistic porosity and permeability will be given to the fractured layers.
4- In order to check the effect of different well/reservoir parameters on water coning in conventional reservoir,
sensitivity analysis for Base Case Conventional Model will be conducted by changing 8 parameters and
simulating the water coning performance for each case. This way, the effect of each parameter will be evaluated
and compared to the Base Model of Conventional Model.
5- In order to check the effect of different well/reservoir parameters on water coning in Naturally Fractured
Reservoir, sensitivity analysis for Base Case Naturally Fractured Model will be conducted by changing 11
parameters and simulating the water coning performance for each case. This way, the effect of each parameter
will be evaluated and compared to the Base Model of Naturally Fractured Model.
6- By this stage, a comprehensive sensitivity analysis has been performed and the effect of different parameters
will be shown for both Conventional Model and Naturally Fractured Model.
7- Since similar sensitivity analysis was conducted for both Conventional Model and Naturally Fractured Model.
A comparison between Conventional Model and Naturally Fractured Model for each sensitivity case. In other
words, because each well/reservoir parameter was changed equally in both model’s sensitivity analysis,
comparison of water coning phenomena in both Conventional Model and Naturally Fractured Model will be
presented.
2.1. Reservoir Simulation Work
The simulation work has been conducted between Conventional Reservoir and Naturally Fractured Reservoir using
ECLIPSE 100 simulator. The simulator is an adaptable dual porosity dual permeability simulator that accounts for
matrixes and fractures, porosity and permeability respectively.
The conventional reservoir radial model comprises of 30 layers in the Z direction and 30 grids in the r direction. A
producing well with a radius of 0.11 m (4.3”) is placed at the center with the producing intervals between layer 1 and 6.
The model is depicted in Figure 1. The reservoir is 500 m in width and 80 meters in depth. There is an active aquifer at
the bottom of the reservoir that is supporting the reservoir in terms of pressure. The top 16 meters of the reservoir has
been perforated in 360 degrees.
The naturally fractured radial model comprises of 59 layers (30 layers of matrix and 29 layers of fractures) in the Z
direction and 30 grids in the r direction. A producing well with a radius of 0.11 m (4.3”) is placed at the center with the
producing intervals between layer 1 and 12. The model is depicted in Figure 1(B). The reservoir is 500 m in width and
80 meters in depth. There is an active aquifer at the bottom of the reservoir that is supporting the reservoir in term of
pressure. The top 16 meters of the reservoir has been perforated in 360 degrees. The natural fracture model is created
with 30 layers of matrix (large layers of low permeability-low porosity) and 29 layers of fracture (small layers of high
permeability-high porosity).
It is important to clarify that both models are having the same porosity, permeability (matrix and fractured layers),
reservoir thickness, water oil contact, aquifer depth, PVT data, well and completion design, oil flowrate (500 m
3
/day),
bottom hole pressure limit (105 Bars), and simulation run period.