Stratigraphic well correlations for 3-D static modeling of carbonate reservoirs

Borgomano, Jean; Fournier, François; Viseur, Sophie; Rijkels, Lex

doi:10.1306/02210807078

Cited by 48 publications

(39 citation statements)

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“…This is the only way to build 3D models which relate the heterogeneity measured at core and well scales to the spatial heterogeneities at reservoir scales (Borgomano et al, 2009). In recent years, these techniques have begun to be applied for tectonic analysis purposes using either subsurface or outcrop data (e.g.…”

Section: Introductionmentioning

confidence: 99%

3D structural modelling of small-deformations in poly-phase faults pattern. Application to the Mid-Cretaceous Durance uplift, Provence (SE France)

Guyonnet‐Benaize¹,

Lamarche²,

Massé³

et al. 2010

Journal of Geodynamics

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Section: Introductionmentioning

confidence: 99%

3D structural modelling of small-deformations in poly-phase faults pattern. Application to the Mid-Cretaceous Durance uplift, Provence (SE France)

Guyonnet‐Benaize¹,

Lamarche²,

Massé³

et al. 2010

Journal of Geodynamics

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“…Although it is not directly measured on wells, it can be deduced through interpretation of the data. As a matter of fact, it has previously been used in the literature for well correlation on real data sets (Massonnat et al, 2002;Gari, 2007;Borgomano et al, 2008;Lallier et al, 2016). The bathymetry was used to identify stratigraphic sequences in the sense of Embry (2002), the sequence boundaries being the maximum regressive surfaces.…”

Section: Application and Implicationsmentioning

confidence: 99%

“…In the forward sense, it has also been shown that several depositional scenarios can produce the same succession of stratigraphic units (Helland-Hansen and Gjelberg, 1994;Armitage et al, 2015;Burgess and Prince, 2015), which motivates the consideration of multiple correlation hypotheses. Even under the same set of hypotheses, correlation lines can be uncertain and are not easily formulated in a systematic and repeatable way when drawn manually by experts (Borgomano et al, 2008;Koehrer et al, 2011;Colombera et al, 2012;Lallier et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

“…Because no reference uncertainty exists, we study the behavior of the obtained stochastic models as the number of wells increases. In complement to previous work which showed the impact of well correlation uncertainty on further reservoir modeling steps (Borgomano et al, 2008;Lallier et al, 2016) and reservoir production behavior (Lallier et al, 2012), we focus this sensitivity analysis on the variability of relative dating of sediments.…”

Section: Introductionmentioning

confidence: 99%

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Uncertainty management in stratigraphic well correlation and stratigraphic architectures: A training-based method

Edwards

Lallier

Caumon

et al. 2018

Computers & Geosciences

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We discuss the sampling and the volumetric impact of stratigraphic correlation uncertainties in basins and reservoirs. From an input set of wells, we evaluate the probability for two stratigraphic units to be associated using an analog stratigraphic model. In the presence of multiple wells, this method sequentially updates a stratigraphic column defining the stratigraphic layering for each possible set of realizations. The resulting correlations are then used to create stratigraphic grids in three dimensions. We apply this method on a set of synthetic wells sampling a forward stratigraphic model built with Dionisos. To perform cross-validation of the method, we introduce a distance comparing the relative geological time of two models for each geographic position, and we compare the models in terms of volumes. Results show the ability of the method to automatically generate stratigraphic correlation scenarios, and also highlight some challenges when sampling stratigraphic uncertainties from multiple wells.

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“…For this purpose, the three-dimensional (3D) stochastic modeling technique is put into use to build a geological model depicting structural features, sedimentary microfacies distribution, and reservoir physical properties to better understand the internal and external characteristics of the reservoir in terms of geometry and distribution of sand bodies, and interrelation between flow units (Qi et al 2007;Guan et al 2010;Nazarpour et al 2014). Borgomano pointed out that the challenge of well correlations is to relate the heterogeneities measured at core and well scales to the spatial heterogeneities at reservoir and flow unit scales (Borgomano et al 2009). 3D geological modeling technology makes use of all the well logging curves not only to preserve the heterogeneity of the tested wells but also to predict certain parameters of flow units with no data (Qi et al 2007;Kohshour et al 2013).…”

Section: Introductionmentioning

confidence: 99%

Geostatistical modeling for fine reservoir description of Wei2 block of Weicheng oilfield, Dongpu depression, China

et al. 2015

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The Wei2 block of Weicheng oilfield is characterized by complicated structure mainly caused by high degree of fault development. Multiple reservoir types are found in this block and the reservoir heterogeneity is severe. The oil and gas reservoirs have already stepped into the stagnant stage of a great water-cut degree together with a rapid production decline rate. Thereby, both stabilizing the oil and gas production and optimizing adjustment for further exploitation make it urgent for geomodelers to build a useful model to predict the inter-well parameters and the distribution of the remaining oil and gas. A three-dimensional geological model established with the help of stochastic modeling technique may provide a perfect window and carrier for fine structure interpretation and reservoir heterogeneity description, compared with a traditional two-dimensional model. Hence, based on stratigraphical layering points, significant surfaces and fault points as well seismic interpretation, an integrated structure model is developed. Using the truncated Gaussian simulation and taking the existing geological maps as references, the sedimentary microfacies model was successfully constructed. Through the use of sequential Gaussian simulation method and the facies-controlled modeling method, the reservoir physical properties are populated. Meanwhile, the comparison between facies-controlled and non-facies-controlled property models indicates that the former is more loyal to previous researching and the representation of heterogeneity is ideal. Finally, the ideas of sample density and reserves fitting are proposed to evaluate the practicability and accuracy of the property models.

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Stratigraphic well correlations for 3-D static modeling of carbonate reservoirs

Cited by 48 publications

References 50 publications

3D structural modelling of small-deformations in poly-phase faults pattern. Application to the Mid-Cretaceous Durance uplift, Provence (SE France)

3D structural modelling of small-deformations in poly-phase faults pattern. Application to the Mid-Cretaceous Durance uplift, Provence (SE France)

Uncertainty management in stratigraphic well correlation and stratigraphic architectures: A training-based method

Geostatistical modeling for fine reservoir description of Wei2 block of Weicheng oilfield, Dongpu depression, China

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