Increasing the predictive power of geostatistical reservoir models by integration of geological constraints from stratigraphic forward modeling

Sacchi, Quinto Renato; Borello, Eloisa Salina; Weltje, Gert Jan; Dalman, R.A.F.

doi:10.1016/j.marpetgeo.2015.10.018

Cited by 21 publications

(8 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Although these results are promising, they are very computationally intensive and may not match dense data sets as provided for instance by seismic data or dense drilling campaigns. Therefore, several studies propose to indirectly integrate information from forward stratigraphic models in static geocellular models (Sacchi et al, 2016). One of the most common methodologies uses forward stratigraphic methods to generate training images for Multiple Point Statistics (MPS) simulation algorithms (e.g., Harris et al (2011)).…”

Section: Cost Computation From a Training Modelmentioning

confidence: 99%

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

Edwards

Lallier

Caumon

et al. 2018

Computers & Geosciences

View full text Add to dashboard Cite

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.

show abstract

Section: Cost Computation From a Training Modelmentioning

confidence: 99%

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

Edwards

Lallier

Caumon

et al. 2018

Computers & Geosciences

View full text Add to dashboard Cite

show abstract

“…Recently, stratigraphic-forward modeling has been used to incorporate quantitative, process-based geologic information to constrain reservoir modeling. For example, Sacchi et al (2016) used a depth-averaged flow in the 2-D horizontal plane, basin-scale stratigraphic-forward model called SimClast Weltje, 2008, 2012) to simulate fluviodeltaic stratigraphic evolution and create a 3-D probability distribution of facies proportions. This probability cube was used as additional input for a geostatistical reservoir model.…”

Section: Introductionmentioning

confidence: 99%

Grain-Size and Discharge Controls on Submarine-Fan Depositional Patterns From Forward Stratigraphic Models

2019

View full text Add to dashboard Cite

Submarine fans are important components of continental margins; they contain a stratigraphic record of environmental changes and host large accumulations of oil and gas. The grain size and volume of sediment supply to fans is thought to control the heterogeneity of deep-water deposits; predicting spatial variability of sandy and muddy deposits is an important applied challenge in the characterization of fans. Here, we use DionisosFlow stratigraphic-forward models to evaluate the sensitivity of submarine-fan deposition to a range of grain sizes, with corresponding diffusion coefficients ranging from 10 to 100 km 2 /kyr for coarse sand to silt/clay, and discharges. In general, finer grains are transported farther in our models because they have larger diffusion coefficients. Coarser grains typical of a sand-rich fan tend to pile up and compensationally stack at the mouth of a proximal feeder channel. Increasing sediment-gravity-flow discharge resulted in a thicker depositional system; however, relatively coarse sediment piled up at the mouth of the feeder channel, which created a slope that promoted basinward sediment transport. Our modeling results can be applied to predict the overall geometry, stacking, and grain-size distribution of submarine fans. Improved understanding of grain-size and discharge controls also informs interpretation of the stratigraphic record of submarine fans. For example, outcrop observations of heterogeneity and compensational stacking of depocenters can be related to changing boundary conditions, namely changes in the caliber and overall supply of sediment delivery to deep-water basin margins.

show abstract

“…Static records include geophysical surveys, well logs and geological data [6] whilst dynamic information provides evidence of the interactions between the static model and the fluid over time. This approach delivers an appropriate means to deal with incomplete datasets [7,8] and has been the standard in oil and gas reservoir modeling for at least three decades [9,10].…”

Section: Introductionmentioning

confidence: 99%

“…Static reservoir modeling is frequently coupled with complementary geophysical techniques. This is because drilling data is characterized by high vertical resolution-low horizontal resolution, whereas geophysical soundings present the opposite pattern [8]. In the case of the former, well logs provide a quantitative method to assess near-borehole petrophysical signatures.…”

Section: Introductionmentioning

confidence: 99%

Water Supply Source Evaluation in Unmanaged Aquifer Recharge Zones: The Mezquital Valley (Mexico) Case Study

Hernández-Espriú

Arango-Galván

Reyes-Pimentel³

et al. 2016

Water

View full text Add to dashboard Cite

Abstract:The Mezquital Valley (MV) hosts the largest unmanaged aquifer recharge scheme in the world. The metropolitan area of Mexico City discharges~60 m 3 /s of raw wastewater into the valley, a substantial share of which infiltrates into the regional aquifer. In this work, we aim to develop a comprehensive approach, adapted from oil and gas reservoir modeling frameworks, to assess water supply sources located downgradient from unmanaged aquifer recharge zones. The methodology is demonstrated through its application to the Mezquital Valley region. Geological, geoelectrical, petrophysical and hydraulic information is combined into a 3D subsurface model and used to evaluate downgradient supply sources. Although hydrogeochemical variables are yet to be assessed, outcomes suggest that the newly-found groundwater sources may provide a long-term solution for water supply. Piezometric analyses based on 25-year records suggest that the MV is close to steady-state conditions. Thus, unmanaged recharge seems to have been regulating the groundwater balance for the last decades. The transition from unmanaged to managed recharge is expected to provide benefits to the MV inhabitants. It will also be likely to generate new uncertainties in relation to aquifer dynamics and downgradient systems.

show abstract

Increasing the predictive power of geostatistical reservoir models by integration of geological constraints from stratigraphic forward modeling

Cited by 21 publications

References 27 publications

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

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

Grain-Size and Discharge Controls on Submarine-Fan Depositional Patterns From Forward Stratigraphic Models

Water Supply Source Evaluation in Unmanaged Aquifer Recharge Zones: The Mezquital Valley (Mexico) Case Study

Contact Info

Product

Resources

About