Summary
An important premise of underbalanced drilling (UBD) is the productivity
improvement it delivers through mitigation of invasive damage. Characterization
and quantification of such damage, therefore, becomes a prerequisite for
assessing the value delivered by UBD. Several methods are available to quantify
damage. In this work, we use a novel approach that combines dynamic microscale
reservoir simulations calibrated to special core tests to model the extent of
invasive damage and its impact on flowback during production. The approach is
based on special tests conducted on the reservoir core and a dynamic
"microsimulator" to model invasion during drilling. Special core tests
designed to measure effects of overbalanced exposure to drilling fluids are
first conducted. Inputs to the simulation model are based on careful
interpretation of the core-test results, and thus are calibrated to
observation. Details of the approach were presented earlier by Suryanarayana et
al. (2007). In this paper, we apply this approach to two field cases and use
the results to quantify the damage and its impact on production. The two field
cases are discussed in detail. Both relative permeability and permanent-damage
effects are described. The dramatic effects of invasion on cleanup and
long-term production are illustrated, demonstrating the incremental value of
UBD in these cases. Damage can be modeled as an equivalent skin, based on the
saturation and permeability profiles within the zone of invasion. Because the
saturation and permeability effects are a function of location along the
productive length and a function of time, we obtain time-dependent and
spatially dependent equivalent skin. The equivalent skin can then be used in
field-scale reservoir models to compare various drilling and development
options. The use of these results in designing an optimal drilling and
completion plan to lock in the value of UBD is demonstrated for the two field
cases.
Introduction
Three distinct advantages of UBD technology can combine to lower the unit
technical cost of a project:
- Reduction in overbalanced-drilling problems
- Reduced formation damage
- Dynamic reservoir evaluation while drilling
However, in low-cost drilling environments, such as land operations in the
Middle East and in North America, drilling-enabling savings from UBD are often
marginal, and the cost of UBD operations becomes an inhibiting factor for wider
implementation because the promise of production enhancement and dynamic
reservoir characterization are not properly quantified. Implementation of UBD
in Russia, Asia, and other low-cost areas will face similar hurdles. The
UBD-implementation predicament is that while we need to prove value to move the
technology forward, we also need data that demonstrate value. Analog
information can be used to develop the business case, but there is a limited
data set because of the perceived high cost of UBD and questionable
effectiveness of the technology in the candidate reservoir. Implementation
costs are driven by use of the equipment, and low usage is driven by a lack of
candidate wells. Even after a successful trial, additional candidates require
cost benefits of commoditization of the technology. But commoditization
requires widespread uptake of the technology, and uptake requires the
recognition of the value. The accepted practice for executing a
"greenfield" development plan is to use a full-field dynamic model to
determine potential value and to use as input into the final investment
decision. However, modeling is often based on unproved initial assumptions
compounded by the lack of UBD well-performance data, so the cycle of
uncertainty repeats. This traps UBD implementation in a "Catch 22"
cycle (illustrated in Fig. 1), which we believe is one reason for its limited
uptake in some areas. In recent times, different approaches have emerged to
quantify UBD value better and to break out of this cycle.
Because damage mitigation is an important value argument for UBD,
quantification of overbalanced-damage effects is an important part of
articulating value from UBD. Invasion damage during overbalanced conditions is
well recognized. However, the implicit presumption when dealing with
invasion-induced damage has been that it can be mitigated (by an appropriate
selection of drilling mud and formation of mudcakes), bypassed (through
perforations), or remedied (through stimulation and fracturing). For this
reason, much of the literature deals with damage remediation, with limited
attention given to the quantification of damage effects.
Damage characterization traditionally has been empirical in nature, being
based on logs, core tests, and buildup tests (Zain and Sharma 2001; Francis
1997; Pang and Sharma 1997; Civan 2000). In recent times, interest has grown in
dynamic simulations to aid quantification of invasion damage and its effect on
flowback (Semmelbeck et al. 1995; Ding and Renard 2003; Wu et al. 2004; Ding et
al. 2004; Suryanarayana et al. 2007). Ding et al. (2004) and Ding and Renard
(2003) propose a comprehensive simulation-based approach that uses core-test
data to specify a length-dependent skin that can be used in numerical
simulation of flowback. Wu et al. (2004) also propose a fine-scale simulation
approach to estimate the distribution of saturation and pressure in the
invasion zone.
Suryanarayana et al. (2007) described a fine-scale, single-well dynamic
simulation approach that is calibrated to special core tests for quantification
of invasive-damage effects. The approach is analogous to that described by Ding
et al. (2004) and Ding and Renard (2003), but it differs in the core-test
specifications, interpretation of core-test results, and simulation methods
used. In this work, we apply the approach described by Suryanarayana et al.
(2007) on two field cases to investigate the post-damage flowback effects. We
first briefly describe the approach used. The two field cases are discussed
thereafter.
© 2009. Society of Petroleum Engineers
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History
- Original manuscript received:
14 August 2006
- Meeting paper published:
16 October 2006
- Manuscript approved:
3 April 2008
- Published online:
16 March 2009
- Version of record:
1 March 2009
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