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 pre-requisite 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 micro-scale reservoir simulations calibrated to special core tests to model the extent of invasive damage, and its impact on flow-back during production. The approach is based on special tests conducted on reservoir core, and a dynamic "micro-simulator" 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. (SPE 95861). 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 clean-up and long-term production are illustrated, thus demonstrating the incremental value of UBD in these cases. Damage can be modelled as an equivalent skin, based on the saturation and permeability profiles within the zone of invasion. Since the saturation and permeability effects are a function of location along the productive length as well as time, we obtain time- and spatially-dependent equivalent skin. The equivalent skin can then be used in field-scale reservoir models to compare different 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 underbalanced drilling (UBD) technology can combine to lower the unit technical cost of a project:Reduction in overbalanced drilling problems,Reduced formation damage, andDynamic 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 a blocker for wider implementation, as 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 dilemma is that while we need to prove value in order to move the technology forward, we also need data that demonstrate value. Analogue information can be used to develop the business case, but there is a limited data set due to perceived high cost of UBD and questionable effectiveness of the technology in the candidate reservoir. Implementation costs are driven by utilization of the equipment and low utilization 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 "green" field development plan is to use a full field dynamic model to determine potential value and use as input into the final investment decision. However, modelling is often based on unproved initial assumptions compounded by the lack of UBD well performance data; and the cycle of uncertainty repeats. This traps UBD implementation in a " Catch 22″ cycle, (illustrated in Figure 1) which we believe is one reason for its limited uptake in some areas. In recent times, different approaches have emerged to better quantify UBD value and break out of this cycle.

No abstract

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 problemsReduced formation damageDynamic 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.