scholarly journals Prediction under Uncertainty in Reservoir Modeling

2002 ◽  
Author(s):  
M. Christie ◽  
S. Subbey ◽  
M. Sambridge
Keyword(s):  
Reservoir Modeling

TRANSIENT MODELING OF CPL FOR TERRESTRIAL APPLICATION, PART B: RESERVOIR MODELING IMPROVEMENT

2014 ◽  
Vol 5 (1-4) ◽  
pp. 271-278
Author(s):  
N. Blet ◽  
Vincent Ayel ◽  
Yves Bertin ◽  
Cyril Romestant ◽  
Vincent Platel
Keyword(s):  
Reservoir Modeling ◽  
Transient Modeling

Integrating The Geophysical Characterization Of Seismic Thin Beds With Stochastic Reservoir Modeling: A Case Study From The Kutei Basin (Offshore Kalimantan, Indonesia)

2011 ◽  
Author(s):  
Giorgio Rocco Cavanna ◽  
Ernesto Caselgrandi ◽  
Elisa Corti ◽  
Alessandro Amato del Monte ◽  
Massimo Fervari ◽  
...  
Keyword(s):  
Reservoir Modeling ◽  
Geophysical Characterization

Coliform transport in a pristine reservoir: modeling and field studies

1998 ◽  
Vol 37 (2) ◽  
pp. 137-144 ◽  
Author(s):  
Elisa Garvey ◽  
John E. Tobiason ◽  
Michael Hayes ◽  
Evelyn Wolfram ◽  
David A. Reckhow ◽  
...  
Keyword(s):  
Model Development ◽  
Fate And Transport ◽  
Field Studies ◽  
Meteorological Conditions ◽  
Reservoir Modeling ◽  
Vertical Circulation ◽  
Quality Model ◽  
Circulation Patterns ◽  
In Situ Experiments

This paper reports on field studies and model development aimed at understanding coliform fate and transport in the Quabbin Reservoir, an oligotrophic drinking water supply reservoir. An investigation of reservoir currents suggested the importance of wind driven phenomena, and that both lateral and vertical circulation patterns exist. In-situ experiments of coliform decay suggested dependence on light intensity and yielded an appropriate decay coefficient to be used in CE-QUAL-W2, a two-dimensional hydrodynamic and water quality model. Modeling confirmed the sensitivity of reservoir outlet concentration to vertical variability within the reservoir, meteorological conditions, and location of coliform source.

A Generalized Compositional Approach for Reservoir Simulation

1983 ◽  
Vol 23 (05) ◽  
pp. 727-742 ◽  
Author(s):  
Larry C. Young ◽  
Robert E. Stephenson
Keyword(s):  
Enhanced Recovery ◽  
Gas Condensate ◽  
Reservoir Modeling ◽  
Pressure Equation ◽  
Compositional Modeling ◽  
Fluid Property ◽  
Black Oil ◽  
Fluid Properties ◽  
Newton Raphson ◽  
Raphson Method

A procedure for solving compositional model equations is described. The procedure is based on the Newton Raphson iteration method. The equations and unknowns in the algorithm are ordered in such a way that different fluid property correlations can be accommodated leadily. Three different correlations have been implemented with the method. These include simplified correlations as well as a Redlich-Kwong equation of state (EOS). The example problems considered area conventional waterflood problem,displacement of oil by CO, andthe displacement of a gas condensate by nitrogen. These examples illustrate the utility of the different fluid-property correlations. The computing times reported are at least as low as for other methods that are specialized for a narrower class of problems. Introduction Black-oil models are used to study conventional recovery techniques in reservoirs for which fluid properties can be expressed as a function of pressure and bubble-point pressure. Compositional models are used when either the pressure. Compositional models are used when either the in-place or injected fluid causes fluid properties to be dependent on composition also. Examples of problems generally requiring compositional models are primary production or injection processes (such as primary production or injection processes (such as nitrogen injection) into gas condensate and volatile oil reservoirs and (2) enhanced recovery from oil reservoirs by CO or enriched gas injection. With deeper drilling, the frequency of gas condensate and volatile oil reservoir discoveries is increasing. The drive to increase domestic oil production has increased the importance of enhanced recovery by gas injection. These two factors suggest an increased need for compositional reservoir modeling. Conventional reservoir modeling is also likely to remain important for some time. In the past, two separate simulators have been developed and maintained for studying these two classes of problems. This result was dictated by the fact that compositional models have generally required substantially greater computing time than black-oil models. This paper describes a compositional modeling approach paper describes a compositional modeling approach useful for simulating both black-oil and compositional problems. The approach is based on the use of explicit problems. The approach is based on the use of explicit flow coefficients. For compositional modeling, two basic methods of solution have been proposed. We call these methods "Newton-Raphson" and "non-Newton-Raphson" methods. These methods differ in the manner in which a pressure equation is formed. In the Newton-Raphson method the iterative technique specifies how the pressure equation is formed. In the non-Newton-Raphson method, the composition dependence of certain ten-ns is neglected to form the pressure equation. With the non-Newton-Raphson pressure equation. With the non-Newton-Raphson methods, three to eight iterations have been reported per time step. Our experience with the Newton-Raphson method indicates that one to three iterations per tune step normally is sufficient. In the present study a Newton-Raphson iteration sequence is used. The calculations are organized in a manner which is both efficient and for which different fluid property descriptions can be accommodated readily. Early compositional simulators were based on K-values that were expressed as a function of pressure and convergence pressure. A number of potential difficulties are inherent in this approach. More recently, cubic equations of state such as the Redlich-Kwong, or Peng-Robinson appear to be more popular for the correlation Peng-Robinson appear to be more popular for the correlation of fluid properties. SPEJ p. 727

Application of geostatistical seismic inversion in reservoir characterization of Sapphire gas field, offshore Nile Delta, Egypt

2019 ◽  
Vol 38 (6) ◽  
pp. 474-479
Author(s):  
Mohamed G. El-Behiry ◽  
Said M. Dahroug ◽  
Mohamed Elattar
Keyword(s):  
Reservoir Characterization ◽  
Nile Delta ◽  
Seismic Inversion ◽  
Reservoir Modeling ◽  
Connectivity Analysis ◽  
Gas Field ◽  
Geostatistical Inversion ◽  
Well Data ◽  
Reservoir Connectivity ◽  
Inversion Techniques

Seismic reservoir characterization becomes challenging when reservoir thickness goes beyond the limits of seismic resolution. Geostatistical inversion techniques are being considered to overcome the resolution limitations of conventional inversion methods and to provide an intuitive understanding of subsurface uncertainty. Geostatistical inversion was applied on a highly compartmentalized area of Sapphire gas field, offshore Nile Delta, Egypt, with the aim of understanding the distribution of thin sands and their impact on reservoir connectivity. The integration of high-resolution well data with seismic partial-angle-stack volumes into geostatistical inversion has resulted in multiple elastic property realizations at the desired resolution. The multitude of inverted elastic properties are analyzed to improve reservoir characterization and reflect the inversion nonuniqueness. These property realizations are then classified into facies probability cubes and ranked based on pay sand volumes to quantify the volumetric uncertainty in static reservoir modeling. Stochastic connectivity analysis was also applied on facies models to assess the possible connected volumes. Sand connectivity analysis showed that the connected pay sand volume derived from the posterior mean of property realizations, which is analogous to deterministic inversion, is much smaller than the volumes generated by any high-frequency realization. This observation supports the role of thin interbed reservoirs in facilitating connectivity between the main sand units.

Reservoir Modeling and Simulation of the Devonian Gas Shale of Eastern Kentucky for Enhanced Gas Recovery and CO2 Storage

2009 ◽  
Author(s):  
Karine Chrystel Schepers ◽  
Brandon C. Nuttall ◽  
Anne Yvonne Oudinot ◽  
Reinaldo Jose Gonzalez
Keyword(s):  
Modeling And Simulation ◽  
Co2 Storage ◽  
Reservoir Modeling ◽  
Gas Shale ◽  
Eastern Kentucky ◽  
Enhanced Gas Recovery ◽  
Gas Recovery

Ground-penetrating radar imaging of Albian rudist buildups, central Texas

2015 ◽  
Vol 3 (3) ◽  
pp. SY67-SY81 ◽  
Author(s):  
Xavier Janson ◽  
Keumsuk Lee ◽  
Chris Zahm ◽  
Charles Kerans
Keyword(s):  
Middle East ◽  
Ground Penetrating Radar ◽  
Reservoir Modeling ◽  
Size Difference ◽  
Seismic Resolution ◽  
Stratigraphic Architecture ◽  
Order Of Magnitude ◽  
Central Texas ◽  
Ground Penetrating ◽  
Subsurface Reservoir

Rudist buildups are important reservoirs in many Cretaceous fields in the Middle East, but they are generally near or below seismic resolution. The dimension, shape, and architecture of rudist buildups can be assessed using outcrop, although only partly so because of pseudo-2D observations of geobodies intersecting with the outcrop. We used ground-penetrating radar to enhance our understanding of the shape, dimension, and architecture of Albian rudist buildups in two outcrops in Texas. In the Lake Georgetown spillway, caprinid rudist buildups are 10–30 m wide and 2–7 m high. They are elliptical with an aspect ratio of as much as 1.7. They show no or very little flank development. The older buildup exposed in the Red Bluff Creek area displays 10- to 25-m-wide and 5- to 10-m-high in situ caprinid rudist mound core accumulations with as much as 100-m-wide reworked flanks in the shallower part of the depositional profile. Downdip along the depositional profile, caprinid buildups are 5–20 m wide and 3–7 m high with no flank debris. The buildups in the Lake Georgetown area have similar architecture and comparable size with the downdip buildups exposed in Red Bluff Creek. These buildups were compared with other outcropping Albian buildups in Texas that have different sizes, shapes, and stratigraphic architecture to provide dimensional data that could be used in subsurface reservoir modeling, either for calibrating variogram ranges or to build training images. The rudist buildups exposed in Texas are an order of magnitude smaller than those present in the subsurface in the Middle East, but they have comparable stratigraphic architecture. The size difference might be the result of subsurface buildups being mapped using well-log or core correlations or seismic extractions that cannot resolved at that scale of heterogeneity.

Stochastic inversion of pressure and saturation changes from time-lapse AVO data

Geophysics ◽  
2006 ◽  
Vol 71 (5) ◽  
pp. C81-C92 ◽  
Author(s):  
Helene Hafslund Veire ◽  
Hilde Grude Borgos ◽  
Martin Landrø
Keyword(s):  
Stochastic Model ◽  
Seismic Data ◽  
Synthetic Data ◽  
Time Lapse ◽  
Bayesian Framework ◽  
Reservoir Modeling ◽  
Data Set ◽  
The North ◽  
Fluid Saturation ◽  
Likelihood Model

Effects of pressure and fluid saturation can have the same degree of impact on seismic amplitudes and differential traveltimes in the reservoir interval; thus, they are often inseparable by analysis of a single stacked seismic data set. In such cases, time-lapse AVO analysis offers an opportunity to discriminate between the two effects. We quantify the uncertainty in estimations to utilize information about pressure- and saturation-related changes in reservoir modeling and simulation. One way of analyzing uncertainties is to formulate the problem in a Bayesian framework. Here, the solution of the problem will be represented by a probability density function (PDF), providing estimations of uncertainties as well as direct estimations of the properties. A stochastic model for estimation of pressure and saturation changes from time-lapse seismic AVO data is investigated within a Bayesian framework. Well-known rock physical relationships are used to set up a prior stochastic model. PP reflection coefficient differences are used to establish a likelihood model for linking reservoir variables and time-lapse seismic data. The methodology incorporates correlation between different variables of the model as well as spatial dependencies for each of the variables. In addition, information about possible bottlenecks causing large uncertainties in the estimations can be identified through sensitivity analysis of the system. The method has been tested on 1D synthetic data and on field time-lapse seismic AVO data from the Gullfaks Field in the North Sea.

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