Simon D. Harris

Schlumberger (British Virgin Islands)

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Q.J. Fisher

University of Leeds

Samita Santoshini

Schlumberger (British Virgin Islands)

A. Levannier

Schlumberger (British Virgin Islands)

Azeddine Benabbou

Schlumberger (British Virgin Islands)

Sheleem Kashem

Schlumberger (British Virgin Islands)

Stewart W. Smith

Schlumberger (Norway)

Thomas Viard

RIKEN Center for Advanced Intelligence Project

Bader Al-Busafi

University of Leeds

Suleiman Al-Hinai

University of Leeds

Danny Povey

Schlumberger (United Kingdom)

Cooperative Institutions

Schlumberger (British Virgin Islands)

University of Leeds

Schlumberger (United Kingdom)

Heriot-Watt University

Heriot-Watt University Malaysia

IFP Énergies nouvelles

NED University of Engineering and Technology

University of Bristol

École Nationale Supérieure des Mines de Nancy

Université de Lorraine

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Ranking and selecting fault models using flow-indicator fault properties and simple streamline simulations

Petroleum Geoscience (2020)

Paul Wilson Stewart W. Smith Danny Povey Simon D. Harris

Fault zones in porous sandstones are commonly divided into two parts: a fault core and a damage zone. Both fault-zone elements could influence subsurface fluid flow and should be incorporated in a geologically realistic model. The fault core can be implemented in the model as a transmissibility multiplier (TM), while the damage zone can be implemented by modifying the grid permeability in the cells adjacent to the model faults. Each of the input parameters used in calculating the TM and damage-zone permeability modification is subject to geological uncertainty. Here an iterative workflow is employed to define probability distribution functions for each of the input parameters, with the result being many fault-model realizations. Here two methods are examined for ranking and selecting the fault-model realizations for further analysis: (i) calculating the flow-indicator fault properties (effective cross-fault transmissibility and effective cross-fault permeability) from the static model; and (ii) employing a simplified flow-based connectivity calculation, returning dynamic measures of model connectivity. The aims are to outline the methodology and workflow used, evaluate the impact of the different input parameters on the results, and examine the results of the static and dynamic approaches to understand how the ranking and selection of models compares between the two. Our results are dependent on the structural model. In a strongly compartmentalized model based on the Gullfaks Field, North Sea, fluid-flow-indicator fault properties are weakly correlated with measures of dynamic behaviour. In particular, models with low fault transmissibility show a much greater range of dynamic behaviour, and are less predictable, than models with high fault transmissibility. In a weakly compartmentalized model with strongly channelized fluvial facies based on the Whitley Bay area in NE England, there was a strong correlation between flow-indicator fault properties and measures of dynamic behaviour. We ascribe these results to the greater complexity of flow paths expected when a highly compartmentalized model contains faults that are likely to be baffles to cross-fault flow. Thematic collection: This article is part of the Fault and top seals collection available at: https://www.lyellcollection.org/cc/fault-and-top-seals-2019

Igneous petrology

10.1144/petgeo2020-017

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Citations (9)

Depogrid: Next Generation Unstructured Grids for Accurate Reservoir Modeling and Simulation

SPE Russian Petroleum Technology Conference (2018)

Samita Santoshini Simon D. Harris Sheleem Kashem A. Levannier Azeddine Benabbou

Abstract As the oil and gas industry is moving toward tapping reserves in more complex structural environments, there comes the challenge for the reservoir modeling platform to accurately and robustly build and simulate a model to aid in making more trustworthy reserve estimates and field development plans. The 3D geocellular model sits at the core of an integrated seismic-to-simulation workflow, within which one can characterize and predict the behavior of reservoirs and can make confident quantitative decisions about one's assets. In structurally complex areas, the construction of accurate 3D models is often impeded by fundamental limitations of standard geocellular modeling technologies. With these limitations in mind, a new cut-cell unstructured grid has been developed that honors the geological structure precisely, enables accurate property modeling in a flattened, un-faulted, pseudo-depositional space, and can be simulated directly in a next-generation simulator; we call this unstructured grid built in depositional space a ‘depogrid’. The polyhedral, cut-cell nature of the depogrid arises when the regularly gridded volume in depositional space is cut by the structural model features (faults and unconformities) before being forward-deformed into geological space. By construction, the grid cell columns are orthogonal to the local stratigraphy, yet they can accurately represent complex structures and volumes, independent of the grid resolution. A next-generation high resolution reservoir seamlessly consumes the globally unstructured grid topology, with the structural complexity and non-neighbor connections, and honors the flow dynamics accurately. This ensures a more geologically consistent simulation model, realistic parameters to tune for history matching workflows and the ability to make reliable predictions. We present some particular reservoir modeling and simulation considerations where the depogrid approach improves on typical gridding technologies. The seismic-to-simulation workflow is then applied to several structural examples to demonstrate how the depogrid is best suited to model the geological structure and properties in a variety of reservoirs and subsequently improves the accuracy and efficiency of field development planning and risk mitigation.

Reservoir Simulation

Unstructured grid

10.2118/191615-18rptc-ms

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Complex Geological Modeling Using Unstructured Grids: Quality Assurance Approaches and Improved Prediction

Simon D. Harris Samita Santoshini Stewart W. Smith A. Levannier Osama Khan

Abstract The vast majority of grids for reservoir modeling and simulation workflows are based on pillar gridding or stairstep grid technologies. The grids are part of a feature-rich and well-established modeling workflow provided by many commercial software packages. Undesirable and significant simplifications to the gridding often arise when employing such approaches in structurally complex areas, and this will clearly lead to poor predictions from the downstream modeling. In the classical gridding and modeling workflow, the grid is built in geological space from input horizon and fault interpretations, and the property modeling occurs in an approximated ‘depositional’ space generated from the geological space grid cells. The unstructured grids that we consider here are based on a very different workflow: a volume-based structural model is first constructed from the fault/horizon input data; a flattening (‘depositional’) mapping deforms the mesh of the structural model under mechanical and geometric constraints; the property modeling occurs in this depositional space on a regular cuboidal grid; after ‘cutting’ this grid by the geological discontinuities, the inverse depositional mapping recovers the final unstructured grid in geological space. A critical part of the depositional transformation is the improved preservation of geodetic distances and the layer-orthogonality of the grid cells. The final grid is an accurate representation of the input structural model, and therefore the quality checking of the modeling workflow must be focused on the input data and structural model creation. We describe a variety of basic quality checking and structurally-focused tools that should be applied at this stage; these tools aim to ensure the accuracy of the depositional transformation, and consequently ensure both the quality of the generated grid and the consistent representation of the property models. A variety of quality assurance metrics applied to the depositional/geological grid geometries provide spatial measures of the ‘quality’ of the gridding and modeling workflow, and the ultimate validation of the structural quality of the input data. Two case studies will be used to demonstrate this novel workflow for creating high-quality unstructured grids in structurally complex areas. The improved quality is validated by monitoring downstream impacts on property prediction and reservoir simulation; these improved prediction scenarios are a more accurate basis for history matching approaches.

Unstructured grid

10.2523/iptc-19303-ms

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Citations (1)

The importance of incorporating the multi-phase flow properties of fault rocks into production simulation models

Marine and Petroleum Geology (2005)

Bader Al-Busafi Q.J. Fisher Simon D. Harris

Reservoir Simulation

Petroleum reservoir

Multiphase flow

Capillary pressure

10.1016/j.marpetgeo.2004.11.003

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Citations (31)

A mixed finite element technique based on implicit discretization of faults for permeability upscaling in fault damage zones

Water Resources Research (2006)

Jingsheng Ma Gary Douglas Couples Simon D. Harris

Natural fault damage zones (FDZs) are often composed of complex arrays containing many thin faults. To account for FDZs in large‐scale models, it is necessary to represent the flow effects of these many small faults by some form of upscaling. The explicit discretization of the geometry and topology of these thin faults and of the rock matrix typically leads to meshes comprising large numbers of elements, making it difficult to solve the flow equations efficiently. This paper proposes a practical technique based on the mixed finite element method (MFEM), permitting the permeability upscaling in two‐dimensional fault damage zones that contain thin and isotropic low‐permeability faults. This technique utilizes an implicit discretization scheme that is similar in principle to those used for discrete fracture networks. The scheme described here treats flow across faults accurately, but, unlike the schemes used for fractures, it neglects the flow along the faults because intrafault volumetric flow in thin faults is very small. This approach allows for a simpler numerical discretization and a reduction in numerical calculation effort. The scheme can be readily implemented in a standard mixed finite element code. Compared with the same MFEM based on an explicit discretization scheme, the two techniques are shown to produce results that agree closely. The implicit technique is shown to be more efficient than the explicit technique for a typical fault damage zone model. This technique is readily extendable to three dimensions.

10.1029/2005wr004686

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Citations (20)

Recent Advances in the Understanding and Incorporation of the Multiphase Fluid Flow Properties of Fault Rocks Into Production Simulation Models

SPE Middle East Oil and Gas Show and Conference (2007)

Suleiman Al-Hinai Q.J. Fisher Carlos A. Grattoni Simon D. Harris Bader Al-Busafi

Abstract For many years it has been common practice to adjust fault transmissibility multipliers within production simulation models to achieve a history match without any scientific justification. In effect, this often means that faults are made ‘scapegoats’ to compensate for inadequacies in reservoir characterisation. In recent years it has become increasingly popular to calculate geologically-realistic transmissibility multipliers based upon measurements of absolute fault permeability and fault rock thickness. A key problem with this method is that it does not take into account the multiphase flow properties (relative permeability and capillary pressure) of fault rocks. This is hardly surprising as the multiphase flow properties of fault rocks are still largely unknown. Here we present measurements that show that under reservoir conditions cataclastic fault rocks may often have maximum gas relative permeabilities that are over two orders of magnitude lower than the undeformed reservoir sandstone adjacent to the fault. Incorporating the multiphase flow properties of faults into production simulation models is still challenging as their static and dynamic properties vary significantly compared with the undeformed reservoir. We review different existing methods for incorporating the multiphase flow properties into simulation models, and we recommend some possible approaches for treating faults that improve on the existing knowledge and software.

Multiphase flow

Cataclastic rock

Relative permeability

Reservoir Simulation

10.2118/105375-ms

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Citations (2)

Fluid-flow properties of faults in sandstone: The importance of temperature history

Geology (2003)

Q.J. Fisher M. Casey Simon D. Harris Robert J. Knipe

Research Article| November 01, 2003 Fluid-flow properties of faults in sandstone: The importance of temperature history Quentin J. Fisher; Quentin J. Fisher 1Rock Deformation Research Group, School of Earth Sciences, University of Leeds, Leeds LS2 9JT, UK Search for other works by this author on: GSW Google Scholar Martin Casey; Martin Casey 1Rock Deformation Research Group, School of Earth Sciences, University of Leeds, Leeds LS2 9JT, UK Search for other works by this author on: GSW Google Scholar Simon D. Harris; Simon D. Harris 1Rock Deformation Research Group, School of Earth Sciences, University of Leeds, Leeds LS2 9JT, UK Search for other works by this author on: GSW Google Scholar Robert J. Knipe Robert J. Knipe 1Rock Deformation Research Group, School of Earth Sciences, University of Leeds, Leeds LS2 9JT, UK Search for other works by this author on: GSW Google Scholar Geology (2003) 31 (11): 965–968. https://doi.org/10.1130/G19823.1 Article history received: 13 May 2003 rev-recd: 04 Aug 2003 accepted: 06 Aug 2003 first online: 02 Mar 2017 Cite View This Citation Add to Citation Manager Share Icon Share Facebook Twitter LinkedIn MailTo Tools Icon Tools Get Permissions Search Site Citation Quentin J. Fisher, Martin Casey, Simon D. Harris, Robert J. Knipe; Fluid-flow properties of faults in sandstone: The importance of temperature history. Geology 2003;; 31 (11): 965–968. doi: https://doi.org/10.1130/G19823.1 Download citation file: Ris (Zotero) Refmanager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentBy SocietyGeology Search Advanced Search Abstract Sandstone rheology and deformation style are often controlled by the extent of quartz cementation, which is a function of temperature history. Coupling findings from deformation experiments with a model for quartz cementation provide valuable insights into the controls on fault permeability. Subsiding sedimentary basins often have a transitional depth zone, here referred to as the ductile-to-brittle transition, above which faults do not affect fluid flow or form barriers and below which faults will tend to form conduits. The depth of this transition is partly dependent upon geothermal gradient. In basins with a high geothermal gradient, fault-related conduits can form at shallow depths in high-porosity sandstone. If geothermal gradients are low, and fluid pressures are hydrostatic, fault-related conduits are only formed when the sandstones have subsided much deeper, where their porosity (and hence fluid content) is low. Mineralization of faults is more likely to occur in areas with high geothermal gradients because the rocks still have a high fluid content when fault-related fluid-flow conduits form. The interrelationship between rock rheology and stress conditions is sometimes a more important control on fault permeability than whether the fault is active or inactive. You do not have access to this content, please speak to your institutional administrator if you feel you should have access.

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10.1130/g19823.1

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Citations (108)

Complex Geological Modeling and Quality Assurance Using Unstructured Grids

Simon D. Harris Samita Santoshini Sheleem Kashem Thomas Viard A. Levannier

Abstract Conceptual limitations of existing gridding technologies often lead to undesirable simplifications to the modeling of structurally complex areas, and consequently poor predictions. We present a structural modeling and gridding workflow that limits these modeling compromises. A volume-based 3D structural model based on fault and horizon surfaces is constructed from input data that has undergone basic quality checking using a variety of techniques. The critical step in the grid creation is the definition of a flattened (‘depositional’) space that deforms the structural model mesh under mechanical constraints. A 3D ‘unstructured’ grid is created in the depositional space, based on ‘cutting’ a property-populated, regular cuboidal grid by the geological discontinuities. The tectonic consistency and better preservation of geodetic distance make the flattened space ideal for a range of property modeling approaches. The forward-deformation of the grid into true geological space tends to preserve the layer-orthogonality of the grid columns and makes the grid more suited to numerical simulation approximations. The final grid is unstructured, high quality and an accurate representation of the input structural model. The 3D structural model, depositional space transform and grid geometries all provide valuable information on the structural quality of the input data. The stretching and deforming of the orthogonal local axes in the transformation from depositional space to geological space are used to focus further effort on structural model quality assurance (QA). The key step in generating accurate property population and simulation models is the application of QA metrics on the grid geometry; the transformation from depositional space to geological space is used to generate a set of grid properties that highlight potential structural inconsistencies or data quality issues back in the structural model. We present several examples based on a range of structurally complex models, and demonstrate the downstream impact of applying this QA workflow throughout the stages of input data validation, structural model creation and grid creation.

Unstructured grid

10.2118/193202-ms

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Citations (12)