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Collaborating Authors
Kline, William E.
Geomechanical Analysis to Evaluate Production-Induced Fault Reactivation at Groningen Gas Field
Sanz, Pablo F. (ExxonMobil Upstream Research Co. (EMURC)) | Lele, Suvrat P. (EMURC) | Searles, Kevin H. (EMURC) | Hsu, Sheng-Yuan (EMURC) | Garzon, Jorge L. (EMURC) | Burdette, Jason A. (ExxonMobil Development Co.) | Kline, William E. (EMURC) | Dale, Bruce A. (ExxonMobil Production Co.) | Hector, Paul D. (ExxonMobil International Ltd.)
Abstract The Groningen Gas Field in Northern Netherlands is the largest gas field in Europe with production starting in 1963. Seismic events were first observed in 1986, but these were generally small with minimal damage. A government study concluded in early 1990โs that tremors were linked to gas production. The objective of the work described here is to utilize advanced geomechanical modeling to (i) characterize subsurface behavior related to production-induced fault reactivation, and (ii) evaluate alternate production strategies to help manage subsurface stresses to reduce fault slippage which can lead to seismicity. Multi-scale 3D geomechanical models were developed using a non-linear quasi-static finite element method. This modeling framework includes a global model to capture full-field phenomena and two sub-models for regions with observed seismic activity which honor conditions of the global model, but also include explicit modeling of multiple faults. This approach considers the following features: i) Irregular stratigraphy and fault surfaces, ii) Variable reservoir rock properties according to porosity changes, iii) Non-uniform pressure depletion derived from field data and reservoir simulations, iv) Relaxed deviatoric salt stresses at start of production, v) Salt creep effects during production, vi) Biot coefficient effects for reservoir rocks, and vii) Coulomb friction behavior to capture slippage along faults. Models are verified by comparing predictions for the production history period (1964 โ 2012) with corresponding field data. The model predictions for production forecast period (2012 onwards) are used for relative comparison of various production scenarios. Subsidence and reservoir strains calculated from the full-field global model during production history match well with corresponding field data without the need for calibration of material properties. Model results show that the fault frictional dissipated energy correlates well with the radiated energy from observed seismic events, and that the energy scaling factor associated with this correlation is constant and the same for both sub-model 1 and 2. The dissipated energy during frictional sliding is a scalar quantity that provides a representative measure of fault activity for a given area of interest. Furthermore, because the dissipated energy correlates well with observed radiated energy, the models can be used for relative comparison of production scenarios to identify strategies that reduce fault loading. Several production forecast scenarios are analyzed and evaluated based on predicted frictional dissipated energy to assess fault slippage. These results indicate that curtailment of production alone is not an effective alternative for mitigation of energy dissipation and related seismic activity. This study shows that advanced geomechanical models are a powerful tool that can provide valuable insight into the overall trend of cumulative radiated energy, are useful in understanding seismic activity, and can be used to identify production scenarios that mitigate seismic activity.
- North America > United States > Texas (0.93)
- Europe > Netherlands > Groningen Province (0.86)
- Geology > Structural Geology > Tectonics > Plate Tectonics > Earthquake (1.00)
- Geology > Geological Subdiscipline > Geomechanics (1.00)
Physics-Based Well Design - Beyond the Learning Curve
Kline, William E. (ExxonMobil Upstream Research Co.) | Chandler, Karen (Exxon Production Research Co.) | Keller, Stuart Ronald (ExxonMobil Upstream Research Co.) | Ottesen, Steinar (ExxonMobil Upstream Research Co.) | Gupta, Vishwas (ExxonMobil Upstream Research Co.) | Tenny, Matthew (ExxonMobil Upstream Research Co.)
Abstract In a drilling program, the design of wells has historically been an incremental process in which compiled experience from previously drilled wells is the principal driver for realizing drilling design. The efficiency of drilling in a field, and as a result, the cost, typically improves significantly initially, before reaching a point at which little improvement is achieved. The progression from the initial well to the final wells of a mature drilling program is often referred to as the "drilling learning curve." Rather than focus on getting the design right after several wells, it is possible to outperform the learning curve by developing and applying fundamental physics-based models and computational optimization engines up front to quantitatively analyze well design options. These proprietary tools have been applied extensively in field development planning, as well as in real-time, to ensure optimal drilling performance. This paper describes ExxonMobil's approach to physics-based modeling, advanced mathematical optimization, and real-time updating to achieve drilling performance that both accelerates and undercuts the historical learning curve. Specific business examples illustrating successful applications of this approach are presented. Introduction Optimal well design requires attention to both fundamental engineering principles and site-specific learnings. The drilling learning curve, which identifies adjustments to initial design parameters to improve overall well design, can frequently cut 50% or more from well costs over the course of a continuous program. While a variety of learning-based well design techniques have served the industry well, the biggest prize is achieved by utilizing physics and mathematics to shift the optimization process from the learning curve to the initial well design โ getting it right the first time. ExxonMobil's approach to going beyond the learning curve is based on routine application of proprietary technology that couples fundamental physics-based models with statistical analyses. The models enable the accurate prediction of expected drilling performance over a wide range of operational conditions. By accounting for downhole parameter uncertainty, engineers effectively optimize this performance over all expected scenarios.
- Asia > Middle East (0.47)
- Asia > Russia > Far Eastern Federal District (0.28)
Physics-Based Well Design - Engineering the Well for Production
Kline, William E. (ExxonMobil Upstream Research Co.) | Dale, Bruce A. (ExxonMobil Upstream Research Co.) | Kumar, Rahul (ExxonMobil Upstream Research Company) | Clingman, Scott (ExxonMobil Upstream Research Company) | Asmann, Marcus (ExxonMobil Upstream Research Company) | Rosenbaum, Darren F. (ExxonMobil Production Co.)
Abstract Ensuring long-term well integrity and optimum completion performance is important for the economic development of any field. However, as fields are now developed with fewer wells and in more technically challenging environments, new technologies are required to deliver mechanically robust and reliable wells that can be operated at the high rates required to meet today's aggressive production targets. Unfortunately, in this environment, our industry can no longer rely on historical industry practices that are based on generalized principles, aggregate historical data, anecdotal evidence, and simplified analytical models, because the inherent inaccuracy of these types of analyses requires excessive use of a significant safety factor between the planned production rates and the actual deliverability limit of the well. To address this challenge, ExxonMobil has developed unique, physics-based, completion design and well performance modeling capabilities that are applied during both well planning and production phases to optimize overall well performance. For example, the ability to accurately model the coupled-physics effects of reservoir compaction, sand production, subsurface shear/slip, completion tubular deformations, and various near-well flow impairment effects enables targeted management of critical mechanical integrity and flow capacity issues. More importantly, these models have provided predictive technologies that have resulted in significant business advantage, as ExxonMobil has developed the capability to quantitatively transform these highly complex issues into well defined, and easily applied "technical limits," which establish the boundaries between conservative, optimum, and potentially detrimental well design and production operations. Practical application has been facilitated by defining these limits in simple terms, including reservoir depletion and/or well drawdown. The incorporation of advanced physics and the corresponding coupled-physics interactions into modeling, simulation and decision-making processes, enables accurate, definition of well performance technical limits and the ability to produce a well right up to these limits. These physics-based production guidance tools provide the technical basis from well design to choke management, enabling more aggressive production with confidence, without risk of failing or impairing wells unnecessarily.
- Well Drilling > Wellbore Design (1.00)
- Well Drilling > Well Planning (1.00)
- Well Drilling > Drilling Operations (1.00)
- (11 more...)