Spatial conditional simulation of facies objects for modeling complex clastic reservoirs

Vargas-Guzmán, J. A.; Al-Qassab, Hisham

doi:10.1016/j.petrol.2006.06.007

Cited by 21 publications

(7 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…How to approach predictions/simulations by geostatistical methods in hydrostatigraphy is a still open question [1][2][3][4][5][6][7][8], since the assessment of the subsoil heterogeneity is one of the keystones in groundwater flow and transport modeling. Different approaches were proposed, e.g., the Boolean [9][10][11], the truncated Gaussian [12] and the pluri-Gaussian simulation methods [13]. However, the most well-known lithological prediction/simulation in classical geostatistics is based on indicator kriging [14][15][16].…”

Section: Introductionmentioning

confidence: 99%

Subsoil Reconstruction in Geostatistics beyond Kriging: A Case Study in Veneto (NE Italy)

et al. 2020

View full text Add to dashboard Cite

The reconstruction of hydro-stratigraphic units in subsoil (a general term indicating all the materials below ground level) plays an important role in the assessment of soil heterogeneity, which is a keystone in groundwater flow and transport modeling. A geostatistical approach appears to be a good way to reconstruct subsoil, and now other methods besides the classical indicator (co)kriging are available as alternative approximations of the conditional probabilities. Some of these techniques take specifically into account categorical variables as lithologies, but they are computationally prohibitive. Moreover, the stage before subsoil prediction/simulation can be very informative from a hydro-stratigraphic point of view, as the detailed transiogram analysis of this paper demonstrates. In this context, an application of the spMC package for the R software is presented by using a test site located within the Venetian alluvial plain (NE Italy). First, a detailed transiogram analysis was conducted, and then a maximum entropy approach, based on transition probabilities, named Markovian-type Categorical Prediction (MCP), was applied to approximate the posterior conditional probabilities. The study highlights some advantages of the presented approach in term of hydrogeological knowledge and computational efficiency. The spMC package couples transiogram analysis with a maximum entropy approach by taking advantage of High-Performance Computing (HPC) techniques. These characteristics make the spMC package useful for simulating hydro-stratigraphic units in subsoil, despite the use of a large number of lithologies (categories). The results obtained by spMC package suggest that this software should be considered a good candidate for simulating subsoil lithological distributions, especially of limited areas.

show abstract

Section: Introductionmentioning

confidence: 99%

Subsoil Reconstruction in Geostatistics beyond Kriging: A Case Study in Veneto (NE Italy)

et al. 2020

View full text Add to dashboard Cite

show abstract

“…To overcome these limitations, efforts have been made to combine geostatistical methods (which is convenient for data conditioning) and process‐based models (which can be used to generate additional realistic data, also called data augmentation) (e.g. Lu et al , ; Vargas‐Guzmán and Al‐Qassab, ; Michael et al , ; Comunian et al , ). For example, Michael et al .…”

Section: Introductionmentioning

confidence: 99%

“…To overcome these limitations, efforts have been made to combine geostatistical methods (which is convenient for data conditioning) and process-based models (which can be used to generate additional realistic data, also called data augmentation) (e.g. Lu et al, 2002;Vargas-Guzmán and Al-Qassab, 2006;Michael et al, 2010;Comunian et al, 2014). For example, Michael et al (2010) used a process-based model to derive statistical attributes, which are then used to simulate the geometry of the deposits with a combination of geostatistical methods.…”

Section: Introductionmentioning

confidence: 99%

Application of 1D paleo‐fluvial process modelling at a basin scale to augment sparse borehole data: example of a Permian formation in the Galilee Basin, Australia

Jiang

Mariethoz

Raiber

et al. 2015

Hydrological Processes

View full text Add to dashboard Cite

The heterogeneous hydraulic conductivity (K) in water‐bearing formations controls subsurface flow and solute transport processes. Geostatistical techniques are often employed to characterize the K distribution in space based on the correlation between K measurements. However, at the basin scale, there are often insufficient measurements for inferring the spatial correlation. This is a widespread problem that we address in this study using the example of the Betts Creek Beds (BCB) in the Galilee Basin, Australia. To address the lack of data, we use a 1D stochastic fluvial process‐based model (SFPM) to quantify the total sediment thickness, Z(x), and the sandstone proportion over the total thickness, Ps(x), in the BCB. The semivariograms of Z(x) and Ps(x) are then extracted and used in sequential Gaussian simulation to construct the 2D spatial distribution of Z(x) and Ps(x). Ps(x) can be converted to a K distribution based on classical averaging methods. The results demonstrate that the combination of SFPM and geostatistical simulation allows for the evaluation of upscaled K distribution with a limited number of K measurements. Copyright © 2015 John Wiley & Sons, Ltd.

show abstract

“…Plurigaussian simulations allow more complex transitions between rock types, based on a truncation rule for a multivariate Gaussian distribution [10]. Applications of plurigaussian simulations have found wide acceptance in the literature [11][12][13][14]. Two and three dimensional arrays of values, having the same statistical and spatial characteristics as rock types or grades of ore deposit, are becoming increasingly useful in the design of advanced exploration/evaluation programs.…”

Section: Introductionmentioning

confidence: 99%

Geological modeling of rock type domains in the Balya (Turkey) lead-zinc deposit using plurigaussian simulation

Yünsel

Ersoy

2013

Open Geosciences

View full text Add to dashboard Cite

Mineral resource evaluation requires defining geological rock-type domains. The traditional simulation methods have serious limitations for applications to large numbers of domains, which have complex contact relations. Plurigaussian simulation is an effective method which can be applied, in a simple way, to any number of domains, using both local and global geological information to infer the distributions of rock types. This work not only presents the application of the plurigaussian simulation method to the Balya lead-zinc deposit, but also assesses the spatially varying rock type proportions, and accounts for uncertainties between them. These parameters are extremely important for mining deposits, since the mineralizations of interest generally occur only in certain rock types. Furthermore, being able to model the different geological rock types is vital to good mine operations, production planning, and management. The results indicate that the plurigaussian method correctly reproduces the different orientations of the individual rock types, as seen in drill holes, and the proportion of each rock type, even if this varies in space.

show abstract

Spatial conditional simulation of facies objects for modeling complex clastic reservoirs

Cited by 21 publications

References 16 publications

Subsoil Reconstruction in Geostatistics beyond Kriging: A Case Study in Veneto (NE Italy)

Subsoil Reconstruction in Geostatistics beyond Kriging: A Case Study in Veneto (NE Italy)

Application of 1D paleo‐fluvial process modelling at a basin scale to augment sparse borehole data: example of a Permian formation in the Galilee Basin, Australia

Geological modeling of rock type domains in the Balya (Turkey) lead-zinc deposit using plurigaussian simulation

Contact Info

Product

Resources

About