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Optimization of Carbonate Stimulation Based on Long-Term Well Performance Predictions_IPTC 13622, 2009

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  Copyright 2009, International Petroleum Technology Conference This paper was prepared for presentation at the International Petroleum Technology Conference held in Doha, Qatar, 7–9 December 2009. This paper was selected for presentation by an IPTC Programme Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the International Petroleum Technology Conference and are subject to correction by the author(s). The material, as presented, does not necessarily reflect any position of the International Petroleum Technology Conference, its officers, or members. Papers presented at IPTC are subject to publication review by Sponsor Society Committees of IPTC. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of the International Petroleum Technology Conference is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of where and by whom the paper was presented. Write Librarian, IPTC, P.O. Box 833836, Richardson, TX 75083-3836, U.S.A., fax +1-972-952-9435.  Abstract Individual wells and their respective completions in the North Field of Qatar are becoming increasingly important and sophisticated. Effective matrix acid stimulation of the very thick, layered carbonate reservoirs plays a key role in achieving and maintaining production targets to meet present and future demand. Completion intervals routinely traverse several layered reservoirs, commingle multiple zones, and span more than a thousand feet in length. The very long intervals give rise to large differences in hydrostatic pressure during stimulation treatments, further complicated by differential reservoir  pressures and rock properties (permeability, porosity, acid reactivity) that change both vertically and areally. In addition to this reservoir complexity, multiple stimulation approaches developed for these high-rate gas wells introduced additional variables in the stimulation design. These included mechanical isolation, chemical diversion, and increased treating rates, all of which carry varying degrees of benefits, costs and risks. Close collaboration between RasGas Company Limited (RasGas) and ExxonMobil has produced a comprehensive toolkit and methodology to effectively stimulate each well and maximize its long-term performance at substantially lower cost and reduced operational risk. The methodology provides an integrated process for quantitatively evaluating and comparing stimulation options in terms of production performance, optimizing these options in reference to physics-based performance limits, and selecting options considering cost, operational complexity, risk, and reward. The theoretical limits discussed in this paper provide a powerful reference capability that can bracket expected performance. A key learning from the study is that stimulation designs can be implemented that allow wells to perform near their “physics limit” at significantly reduced cost and considerably lower operational risk than previously understood. Introduction The North Field is the largest non-associated gas field in the world with estimated reserves exceeding 900 TCF. Qatar's  North Field energy resources and RasGas’ role in extracting and distributing those resources have significant impact on the global LNG market. Industry experts estimate that Qatar will supply 25-30 per cent of the world's LNG by 2010. RasGas will produce, process, and ship almost one-half of Qatar's LNG. As part of this rapid expansion of the North Field development, RasGas has drilled and completed nearly 100 wells over the past five years. The main completions objective is to construct long-lived wells that maximize wellbore deliverability at reduced cost, while increasing reliability and decreasing operational risk. To achieve this objective in the North Field, effective matrix acid stimulation is of critical importance. Completion intervals in RasGas wells routinely traverse several layered reservoirs, commingle multiple zones, and span more than a thousand feet in length. The very long intervals give rise to large differences in hydrostatic pressure during stimulation treatments, further complicated by differential reservoir pressures and rock properties that change both vertically and areally (e.g., permeability, porosity, acid reactivity, etc.). IPTC 13622 Optimization of Carbonate Stimulation based on Long-Term Well Performance Predictions D. Postl, T.K. Ellison, D. Chang, C.E. Shuchart, ExxonMobil Upstream Research Company, Arnout Mols, ExxonMobil Production Company, N. Nor, H. Alkharaz, A. Valle, C.J. Sieben, R. Chintaluri, Z. Wang, L. Sanchez,  A. Farah, RasGas Company Limited  2 IPTC 13622 ExxonMobil and RasGas had previously developed a successful stimulation methodology 1  for the “shorter” completion intervals (several hundreds of feet) encountered in the early stages of development. For longer completion intervals, this methodology was adapted to employ retrievable mechanical isolation devices (i.e., plugs) to break the completion interval into shorter sections, followed by implementation of the techniques and methods that were already proven successful for the shorter completions. The use of mechanical plugs introduced several operational challenges which included setting and unsetting the plug in the large diameter production liner, withstanding pressures in an acid environment, and a large number of wireline runs. Despite the increased operational risks and costs, the use of retrievable plugs was initially considered necessary for all longer completion intervals given the importance of effective stimulation throughout the completed interval. Collaboration between ExxonMobil and RasGas led to the development of multiple alternative stimulation technologies 2 .  Numerous advancements were made in the areas of chemical diversion, perforation strategies, plugless mechanical diversion, high-rate pumping, and increased stimulation vessel capacities. Subsequently, it became apparent that more advanced modeling tools and analysis techniques were required to adequately assess the risks and rewards associated with the various options that emerged as part of a growing stimulation toolkit. Much of the industry’s focus in the completions/stimulation area had been on utilizing relatively simple “skin factor” optimization methods to treat wells with the objective of maximizing initial well performance without adequate consideration of long-term productivity. Integration of the long-term relative depletion performance with alternative stimulation designs had previously not been rigorously accounted for in the  process of optimizing carbonate stimulation treatments. In this paper, a new methodology is presented. This methodology, which is schematically illustrated in Figure 1, is based on the recognition that “skin factor” alone is an inadequate metric for stimulation success in multi-layer reservoirs, and that long-term performance and other metrics are required. The methodology accounts for layer-by-layer distribution of skin and relative comparison with the theoretical best performance governed by acidization physics and reservoir drivers. Figure 1 depicts the three main elements of this methodology: (1) detailed stimulation modeling, considering both in-well and near-well phenomena; (2) well performance prediction, both initially as well as through time; and (3) stimulation option selection. Stimulation optimization is achieved via an integrated process for quantitatively evaluating stimulation options in terms of  production performance, comparing the options against physics-based performance limits, and selecting options considering cost, operational complexity, risk, and reward. This optimization methodology has been applied to North Field wells and has become the standard practice when developing the stimulation strategy and designs for each new completion. Results have shown that wells stimulated using this approach  perform near their “physics limit” at significantly reduced cost 3,4  and considerably lower operational risk than previously understood. This methodology was a key enabler to evaluate different completion designs. Thus, it showed that as a result of the advancements in plugless stimulation technologies, plugless designs often resulted in similar performance to the designs using plugs. Figure 1. Process for optimizing carbonate stimulation based on long-term well performance Detailed Stimulation Modeling The first element of the present optimization methodology is linked to the overall stimulation strategy 1  that enabled ExxonMobil and RasGas to successfully complete approximately 40 production wells in the timeframe between 1998 and 2005. This strategy relies heavily on sophisticated modeling capabilities that permit accurate predictions of complex stimulation treatments in long carbonate completion intervals. ExxonMobil’s carbonate matrix acidizing (CMA) tool employs a single-well modeling approach that honors near-well characteristics based on foot-by-foot descriptions of  permeability, porosity, lithology, and reservoir pressure.    F   B   H   P Time TheoreticalPluglessPlug Option 2Option 1Option 3Option 4Detailed Stimulation ModelingOption SelectionWell Performance Prediction  AcidDiverter    FBHP Relative to Theoretical Operational Risk    F   B   H   P Time TheoreticalPluglessPlugTheoreticalPluglessPlug   Option 2Option 1Option 3Option 4Detailed Stimulation ModelingOption SelectionWell Performance Prediction  AcidDiverter    FBHP Relative to Theoretical Operational Risk Production Liner   IPTC 13622 3  Acid Placement Optimization: Theoretical Reference States As a key component of the CMA tool, a semi-empirical wormhole model 5  provides layer-specific wormhole predictions as a function of acid volume, treatment rate, and rock properties. The model has been thoroughly validated and calibrated with  both laboratory core studies and field data. Continued advancement of ExxonMobil’s wormhole prediction technologies led to the development of a “physics limit” reference capability that provides theoretically optimized wormhole length  predictions for a given acid volume without the need for simulating the dynamics of the acidizing process. This capability, which assumes acid injection at the optimum flux at all points in time, is based on the same governing equations as used in the underlying wormhole model. The resulting analytical model equations provide the basis for mathematical optimization algorithms that were developed to determine idealized acid placement strategies based on a variety of objective functions. The first theoretical reference state is based on the mathematical objective of minimizing the total (average) well skin for a given acid volume (i.e., achieving the maximum negative skin). The second theoretical reference state is based on the objective of maximizing connectivity to reservoir porosity ( φ -h) by increasing the productivity of low permeability, high  porosity layers. In both cases, operational constraints are deliberately removed from the analysis. In contrast to traditional modeling approaches that predict the distribution of acid as a result of actual stimulation treatments (which would account for multiple fluid stages, changing injection rates, as well as mechanical and/or chemical diversion), this capability enables a- priori  determination of target volumes on a layer-by-layer basis. The implications of applying these algorithms to long completion intervals in North Field wells are illustrated in Figure 2. Shown on the left-hand-side are representative permeability (k-h) and porosity ( φ -h) distributions. Note that the higher- permeability zones mostly consist of dolostone layers (DS), while much of the porosity is concentrated in the limestone layers (LS). Acid distributions based on the mathematical optimization algorithms are shown on the right-hand side of Figure 2. Placement based on the objective of minimizing the overall well skin causes the acid to be naturally “drawn” to the higher k-h zones (due to the k-h averaged nature of the objective function). The higher porosity LS layers are stimulated only marginally. On the flipside, if acid placement is optimized with respect to maximizing connectivity to porosity, the lower  permeability LS layers are preferentially targeted to increase their post-stimulation productivity relative to the higher  permeability DS layers. Figure 2. Theoretical acid distributions: typical permeability, porosity distribution (left); acid placement based on mathematical optimization algorithms (right) The theoretical acid distributions described above not only provide a powerful reference capability that facilitates design and evaluation of actual stimulation treatments, they also highlight the conceptual differences in stimulation objectives based on reservoir characteristics and possible depletion scenarios. The strategy employed in stimulating a particular well would be considerably different if either one or the other of the two distributions were chosen as the stimulation target. This understanding led to the recognition that well performance prediction, both initially as well as through time, needed to be included in the overall stimulation strategy 4 . 0%25%50%75%100%1-DS2-DS3-DS4-DS5-LS6-DS7-DS8-LS9-DS    L  a  y  e  r  s % Acid Volume Minimize AverageWell SkinMaximize Connectivityto Porosity 0%25%50%75%100% 1-DS2-DS3-DS4-DS5-LS6-DS7-DS8-LS9-DS       L     a    y     e     r     s % k-h / phi-h %k-h%phi-h  4 IPTC 13622 Well Performance Prediction Productivity Based Stimulation Prior to the development of the new modeling tools and analysis capabilities presented in this paper, the focus of the North Field stimulation strategy was to ensure aggressive acidization of every formation layer in the completion interval. Although the results of this approach had consistently been shown to be favorable, the cost and operational risk associated with such aggressive stimulation was often greater than desired. As part of the collaboration between ExxonMobil and RasGas 2 , a comprehensive effort was undertaken to understand the effects of deviating from the srcinal stimulation strategy and employing emerging plugless stimulation technologies on a case-by-case basis. Much of the initial focus was directed toward identifying the degree of difficulty associated with ensuring aggressive stimulation of all layers in each individual well. Subsequently, the relative productivity benefit obtained from this aggressive stimulation approach was compared to the complexity of the stimulation strategy. One of the key learnings from this effort is illustrated in Figure 3. In the North Field, the difficulty of effectively stimulating the upper zones of long, multi-layer completion intervals increases with decreasing  permeability of the upper zones. Stimulation of the upper zones can be further complicated by differential depletion between the zones (i.e., if the lower reservoirs are lower pressure). The relative benefit, however, does not necessarily follow the same trend, especially with regard to the distribution of a well’s permeability. From a productivity standpoint, the relative importance of the upper zones increases with increasing permeability. While these results may seem intuitively obvious, they suggested that the use of mechanical plugs for enhanced diversion may not be required for all wells, and that the incremental  benefits derived from the added cost and risk may not always be warranted. Based on this understanding, focus was directed towards developing long-term productivity-based stimulation objectives. Although the expectation was clear – results comparable to what could be accomplished with mechanical isolation – the tools were needed to quantitatively compare stimulation options in terms of long-term production performance and against the “physics limit” reference states described above. Figure 3. Difficulty associated with stimulating all zones in long, layered completion intervals  Development of a Single-Well Inflow Performance Analysis Tool The decision to pursue the development of well-performance based analysis tools for selecting stimulation strategies was  primarily driven by two factors: (1) the need for productivity-based stimulation objectives for each well, and (2) the recognition that long-term reservoir drivers need to be accounted for in the early stages of selecting a well’s stimulation strategy. The second element, in particular, proved to be of particular importance given the learnings associated with the “physics limit” concepts outlined in Figure 2. Optimal placement of acid across long completion intervals would require detailed knowledge of various reservoir characteristics, most notably permeability prediction, vertical communication, and reservoir pressures. Referring back to the discussion of the theoretical reference states, the two optimization algorithms would collapse onto a single acid distribution if all near-well formation layers were modeled to be in full vertical communication in the reservoir. In wells completed in very thick carbonate formations spanning several reservoirs, such as the North Field, this is likely not the case. Through close collaboration between stimulation experts and reservoir engineers, a stimulation analysis tool was developed with specific focus on the linkage between the well and the reservoir. Detailed in-well and near-well flow models, designed to account for the bulk of the pressure drops in and around the completion, were integrated with existing stimulation design tools. These models were then combined with the aforementioned “physics limit” reference capabilities and linked to the reservoir via dynamic pressure boundary conditions supplied from full field model simulations or specifically modified to evaluate sensitivities. The resulting single-well modeling tool, which incorporates nodal-analysis as schematically illustrated in Figure 4, was primarily designed to facilitate rapid evaluations of reservoir and stimulation uncertainties. The modeling is       T      V      D Formation Pressure% kh Zone 1Zone 2       T      V      D Formation Pressure% kh Zone 1Zone 2 Difficultyof Reaching Stimulation Targets in Upper Zones         T      V      D Formation Pressure% kh Zone 1Zone 2       T      V      D Formation Pressure% kh Zone 1Zone 2 Difficultyof Reaching Stimulation Targets in Upper Zones
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