"Coupled" Stress/Fluid/Thermal Multi-Phase Reservoir Simulation Studies 
Incorporating Rock Mechanics

Koutsabeloulis, Nick; Smart, Brian George Davidson; Somerville, James McLean; Minton, J.; Bradvedt, K; Bucholz, C

doi:10.2523/47393-ms

Cited by 19 publications

(13 citation statements)

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“…The cooling effects of injected water can cause the faults to become critically stressed or reactivated (Barton et al 1995;Heffer et al 1995;Koutsabeloulis & Hope 1998). Significant drilling fluid losses can occur in and around faults in late field life that originally had no impact on drilling in early field life.…”

Section: Structural Reservoir Descriptionmentioning

confidence: 98%

“…However, whilst it is unlikely that we will ever be able to predict actual individual fault and fracture distributions at the core scale across a reservoir, there have been advances in developing analytical proxies. The advent of high performance computing capability enables advances in numerical geomechanical modelling techniques together with rock property studies (Koutsabeloulis & Hope 1998;Nieuwland 2003;Zhang et al 2007). Resulting numerical stress and strain simulation and forward prediction capabilities offer the opportunity to better model the spatial distribution of the processes controlling the formation of faults and fractures (McClay et al 2002;Main et al 2007;Wilkins 2007).…”

Section: Structural Reservoir Descriptionmentioning

confidence: 99%

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The challenges and impact of compartmentalization in reservoir appraisal and development

Fox

Bowman

2010

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As an industry we have been poor at identifying and predicting the effect of reservoir compartmentalization on fluid flow throughout field life. In the context of harder-to-find reserves and rising development costs it is vital to have a well-rounded strategy in place to identify and mitigate uncertainties and risks associated with compartmentalization. The key challenge of today is therefore to improve predictive capability.Historically we have relied too heavily on 'single complex' linear modelling approaches to understand the impact of compartmentalization. Lately, we have begun to place a greater emphasis on using a forensic level of reservoir analysis coupled with the use of dynamic signals from production data and constant down hole monitoring of fluid-type, pressures and temperatures. Evidence is mounting that as fields deplete they evolve mechanically over production time-scales leading to changes in fault behaviour, stress configuration, compaction and hence compartmentalization; such factors are commonly not predicted at start-up. Our challenge has been to develop toolkits and workflows which integrate an appropriate range of geological models iteratively coupled with dynamic data. We need to develop analytical approaches that enable real-time updates from the evolving reservoir & fluid system to iteratively modify our models and improve their predictive power. This will allow us to make better-informed decisions at every stage of field life.The upstream exploration and production business is commonly driven by the expectation that we can now get more from our older existing fields, continue with positive reserve replacement ratios (the ratio between: reserves booked from discoveries, field extensions and improved recovery schemes; and production over a given period), manage rising costs, and make better informed decisions when faced with increased geological complexity in new developments. Thus, production teams are pressured to deliver on promises derived from geological models and production rate profiles experienced and/or predicted earlier in a field's Appraisal or Development phase. There are, however, many examples in the literature where compartmentalization has unexpectedly impacted field development (e.g. Gainski et al. 2010;McKie et al. 2010). It follows that successful production optimization is controlled by our ability to characterize and predict reservoir performance and fluid flow behaviour over the life-cycle of a hydrocarbon field. In many cases, this understanding comes through experience, relatively late in field life (e.g. Barkved et al. 2003;Clifford et al. 2005;Moulds et al. 2005;Barr et al. 2007;Gainski et al. 2010). Understanding the impact of compartmentalization on fluid flow and the ability to predict it prior to drilling wells is a long-term intention of many companies, but it is consistently under-evaluated and underestimated. It would appear that we still have some way to go before we consistently predict the impact of faults, fractures, stress and other reservoir heteroge...

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Section: Structural Reservoir Descriptionmentioning

confidence: 98%

Section: Structural Reservoir Descriptionmentioning

confidence: 99%

The challenges and impact of compartmentalization in reservoir appraisal and development

Fox

Bowman

2010

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“…Geomechanical fluid flow simulations with a consolidation mode were conducted to predict the changes in stresses during production using coupled geomechanical modeling (Koutsabeloulis and Hope 1998;Koutsabeloulis and Zhang 2009). During the entire production schedule, the change in pressures, permeability, and effective stresses were calculated based on the initial pressure, porosity, and permeability.…”

Section: Coupled Geomechanical Simulation For Depletion and Injectionmentioning

confidence: 99%

Modelling of Depletion-Induced Microseismic Events by Coupled Reservoir Simulation: Application to Valhall Field

Zhang

Koutsabeloulis

Kristiansen

et al. 2011

SPE EUROPEC/EAGE Annual Conference and Exhibition

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Reservoir depletion/injection results in changes in effective stress, which may cause formation failure, propagation of existing fractures/faults and initialisation of new fractures/faults. A flow-deformation coupled reservoir geomechanical modelling approach has been applied to compute the change in reservoir effective stress and associated propagation of fractures and reactivation of faults. The computed inelastic strain change was used to predict the magnitudes of microseismic emissions associated with fault reactivations. The moment magnitude of microseismic events, consistent with the Richter scale, can be computed from the scalar value of their moment tensor. In a discontinuous model, the moment tensor can be calculated directly; in finite element models, the moment tensor is calculated by integrating the change in inelastic shear strain over the volume of the elements containing the failed fault. Coupled 3D geomechanical (deformation and fluid flow) simulations for Valhall field were conducted. Well rate and reservoir pressure histories were used as inputs to simulate reservoir depletion/injection. The 99 faults visible on seismic interpretations and 22 subregional fracture sets were included in the model. An elasto-inelastic cap model including water-weakening mechanism was used to model the chalk reservoir; the failure of faults and fractures were simulated by Mohr-Coulomb criterion. Prior to performing production simulation, preproduction stress modelling was carried out to reach an equilibrium stress state that was consistent with the in-situ condition, in terms of magnitude and orientation. Then, oil production at 112 wells and water injection at 15 wells for the period from 1982 to 2006 were simulated, during which the simulated microseismic events were in a good agreement with observations. The computed formation deformation in the reservoir and overburden was related to the in situ stress and faulting structure and was correlated over long distances. These characteristics are indicative of a near-critical process (and are also observed in flow rate correlations in the field). The coupled 3D geomechanical simulation provides a tool for validating modelled reservoir geomechanical effects against specific field data, and so enhances confidence in the implications predicted for drilling operations and reservoir management. IntroductionUnder most circumstances, an oil or gas field may be described as a system of rock blocks with fluids, partially separated by faults and fractures. Field evidence has been growing that the interaction between reservoir rock deformation and fluid flow is an intrinsic component of the system behaviour over the development life of a reservoir. In previous studies (Zhang et al. 2007a(Zhang et al. , 2007b, three key features-long-range correlation, stress-relationship, and fault-relationship-were observed in correlations in fluctuations of well flow rates when the stress state in a field was at or close to a critical state. This is because when field stress state prior to depl...

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“…mechanical-hydraulic) is essential for the understanding of reservoir performance, such as depletion/injection activities in an oil/gas field (Koutsabeloulis and Zhang, 2009). In this case, a two-way coupled reservoir geomechanical modeling approach is required (Koutsabeloulis and Hope, 1998) to compute the change in reservoir pore pressure distribution, stress state and strain development, fracture permeability change, and the evolution of reservoir properties.…”

Section: Introductionmentioning

confidence: 99%

Estimate of Permeability of Fracture Corridors/Networks: from Data Acquisition to Reservoir Simulations

Zhang

Koutsabeloulis

2010

All Days

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An empirical flow model, based on the observed fracture networks and corridors of the deepwater clastic systems of Clare Basin, Ireland, shows that fracture enlargement at intersections increases the vertical flow through fracture corridors. In vertical fracture corridors, flow is dominantly controlled by fracture density and aperture, but this work also shows a significant influence from fracture intersection openings.Only connected fracture networks contribute to field horizontal permeability, while both isolated and connected fractures contribute to vertical permeability. In this field, horizontal fracture flow needs a minimum fracture density about 4.5 m -1 ; below that critical density, no field horizontal fracture flow exists. For fracture aperture of 0.1 mm, field horizontal intrinsic fracture permeability can be estimated by an empirical equation: k IH (cm 2 ) = 5x10 -9 d 3.802 (m -1 ) for fracture density between 4.5 and 7 m -1 ; where fracture density is between 7 and 20 m -1 , the empirical equation k IH (cm 2 ) = 2x10 -7 d 1.978 (m -1 ); where fracture density is above 20 m -1 , k IH is close to field vertical intrinsic fracture permeability (k IV ) because more and more fractures are connected to form flow channels.The workflow introduced here estimates field scale-fracture permeability using discrete fracture networks (DFNs) for reservoir simulations from seismic and well logs. We estimated the vertical permeability of both simulated fracture networks and natural fracture networks from the sediment rock exposures in the English Lake District, estimating both vertical and horizontal intrinsic fracture permeabilties based on fracture density (d).

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"Coupled" Stress/Fluid/Thermal Multi-Phase Reservoir Simulation Studies Incorporating Rock Mechanics

Cited by 19 publications

References 0 publications

The challenges and impact of compartmentalization in reservoir appraisal and development

The challenges and impact of compartmentalization in reservoir appraisal and development

Modelling of Depletion-Induced Microseismic Events by Coupled Reservoir Simulation: Application to Valhall Field

Estimate of Permeability of Fracture Corridors/Networks: from Data Acquisition to Reservoir Simulations

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