Carbonate Geobodies: Hierarchical Classification and Database – A New Workflow for 3d Reservoir Modelling

Jung, A.; Aigner, Thomas

doi:10.1111/j.1747-5457.2012.00518.x

Cited by 33 publications

(30 citation statements)

References 44 publications

(42 reference statements)

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“…However, the initial depositional texture also profoundly influences the stratabound dolostone geobodies; therefore, the depositional classification of geobodies of Jung and Aigner (2012) can be applied to this type of diagenetic geobodies (stratabound geobodies at Wadi Mistal would correspond in this classification to a Jurassic ramp system in the protected platform zone and with a "sheet" shape, see Table 1A). …”

Section: Control On Dolomite Geobody Dimensions Diagenetic Geobody Cmentioning

confidence: 99%

“…Several studies such as Harris et al (2011) focused on quantifying dimensions of carbonate sand bodies and their spatial patterns. Recent efforts led to a hierarchical classification scheme of carbonate geobodies and a set of rules to characterize their dimension, shape, orientation and spatial distribution as a basis for reservoir modeling (Jung and Aigner, 2012). Components of this classification scheme includes geological time, system, zone, shape, element and facies of deposition (Jung and Aigner, 2012).…”

Section: Introductionmentioning

confidence: 99%

“…Recent efforts led to a hierarchical classification scheme of carbonate geobodies and a set of rules to characterize their dimension, shape, orientation and spatial distribution as a basis for reservoir modeling (Jung and Aigner, 2012). Components of this classification scheme includes geological time, system, zone, shape, element and facies of deposition (Jung and Aigner, 2012). Aside from shape, all of the components in the Jung and Aigner (2012) classification are related to sedimentology and depositional environment; diagenetic geobodies are not taken into consideration (Table 1A).…”

Section: Introductionmentioning

confidence: 99%

“…Components of this classification scheme includes geological time, system, zone, shape, element and facies of deposition (Jung and Aigner, 2012). Aside from shape, all of the components in the Jung and Aigner (2012) classification are related to sedimentology and depositional environment; diagenetic geobodies are not taken into consideration (Table 1A).…”

Section: Introductionmentioning

confidence: 99%

“…We then combine this dataset with a structural analysis, and compare the above dataset to the geobodies dimensions, shape and distribution in order to assess how processes impact on geobody dimensions and geometries. This leads us to propose a simple modification to the Jung and Aigner (2012) classification for geobodies for the purpose of reservoir modeling.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Linking process, dimension, texture, and geochemistry in dolomite geobodies: A case study from Wadi Mistal (northern Oman)

Vandeginste¹,

John²,

Flierdt³

et al. 2013

Bulletin

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Understanding the distribution and geometry of reservoir geobodies is crucial for netto-gross estimates and to model subsurface flow. This paper focuses on the process of dolomitization and resulting geometry of diagenetic geobodies in an outcrop of Jurassic host rocks from northern Oman. Field and petrographic data show that a first phase of stratabound dolomite is crosscut by a second phase of fault-related dolomite. The stratabound dolomite geobodies are laterally continuous for at least several hundreds of meters (~1000 ft) and probably regionally and are half a meter (1.6 ft) thick. Based on petrography and geochemistry, a process of seepage reflux of mesosaline or hypersaline fluids during the early stages of burial diagenesis is proposed for the formation of the stratabound dolomite. In contrast, the fault-related dolomite geobodies are trending along a fault that can be followed for at least 100 Running head:Linking process, dimension, texture and geochemistry in dolomite geobodies

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Section: Control On Dolomite Geobody Dimensions Diagenetic Geobody Cmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Linking process, dimension, texture, and geochemistry in dolomite geobodies: A case study from Wadi Mistal (northern Oman)

Vandeginste¹,

John²,

Flierdt³

et al. 2013

Bulletin

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Uncertainty in training image‐based inversion of hydraulic head data constrained to ERT data: Workflow and case study

Hermans

Nguyen

Caers

2015

Water Resources Research

106

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In inverse problems, investigating uncertainty in the posterior distribution of model parameters is as important as matching data. In recent years, most efforts have focused on techniques to sample the posterior distribution with reasonable computational costs. Within a Bayesian context, this posterior depends on the prior distribution. However, most of the studies ignore modeling the prior with realistic geological uncertainty. In this paper, we propose a workflow inspired by a Popper-Bayes philosophy that data should first be used to falsify models, then only be considered for matching. We propose a workflow consisting of three steps: (1) in defining the prior, we interpret multiple alternative geological scenarios from literature (architecture of facies) and site-specific data (proportions of facies). Prior spatial uncertainty is modeled using multiplepoint geostatistics, where each scenario is defined using a training image. (2) We validate these prior geological scenarios by simulating electrical resistivity tomography (ERT) data on realizations of each scenario and comparing them to field ERT in a lower dimensional space. In this second step, the idea is to probabilistically falsify scenarios with ERT, meaning that scenarios which are incompatible receive an updated probability of zero while compatible scenarios receive a nonzero updated belief. (3) We constrain the hydrogeological model with hydraulic head and ERT using a stochastic search method. The workflow is applied to a synthetic and a field case studies in an alluvial aquifer. This study highlights the importance of considering and estimating prior uncertainty (without data) through a process of probabilistic falsification.

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Training Image Construction

Mariethoz

Caers

2014

Multiple‐Point Geostatistics

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Carbonate Geobodies: Hierarchical Classification and Database – A New Workflow for 3d Reservoir Modelling

Cited by 33 publications

References 44 publications

Linking process, dimension, texture, and geochemistry in dolomite geobodies: A case study from Wadi Mistal (northern Oman)

Linking process, dimension, texture, and geochemistry in dolomite geobodies: A case study from Wadi Mistal (northern Oman)

Uncertainty in training image‐based inversion of hydraulic head data constrained to ERT data: Workflow and case study

Training Image Construction

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