Gregoire Mariethoz | University of Lausanne (original) (raw)
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Papers by Gregoire Mariethoz
In this paper, we propose a new cosimulation algorithm for simulating a primary variable using on... more In this paper, we propose a new cosimulation algorithm for simulating a primary variable using one or several secondary attributes known exhaustively on the domain. At each node of the grid to be simulated, two conditional distribution functions are inferred. The first one comes from the available conditioning data of the main attribute using, for instance, a multi-Gaussian framework. The
Inverse modeling which transforms obtained geophysical data into physical properties of the Earth... more Inverse modeling which transforms obtained geophysical data into physical properties of the Earth is an essential process for reservoir characterization. We propose a Markov chain Monte Carlo (McMC) workflow consistent with geology, well-logs, seismic data and rock-physics information. The workflow uses Direct Sampling (DS), a multiple-point geostatistical method, for generating realizations from the prior distribution and Iterative Spatial Resampling (ISR)
Second EAGE Integrated Reservoir Modelling Conference, 2014
Second EAGE Integrated Reservoir Modelling Conference, 2014
Water Resources Research, 2014
ABSTRACT We develop a stochastic approach to construct channelized 3D geological models constrain... more ABSTRACT We develop a stochastic approach to construct channelized 3D geological models constrained to borehole measurements as well as geological interpretation. The methodology is based on simple 2D geologist-provided sketches of fluvial depositional elements, which are extruded in the 3rd dimension. Multiple-point geostatistics (MPS) is used to impair horizontal variability to the structures by introducing geometrical transformation parameters. The sketches provided by the geologist are used as elementary training images, whose statistical information is expanded through randomized transformations. We demonstrate the applicability of the approach by applying it to modeling a fluvial valley filling sequence in the Maules Creek catchment, Australia. The facies models are constrained to borehole logs, spatial information borrowed from an analogue and local orientations derived from the present-day stream networks. The connectivity in the 3D facies models is evaluated using statistical measures and transport simulations. Comparison with a statistically equivalent variogram-based model shows that our approach is more suited for building 3D facies models that contain structures specific to the channelized environment and which have a significant influence on the transport processes.
In this paper, we propose a new cosimulation algorithm for simulating a primary variable using on... more In this paper, we propose a new cosimulation algorithm for simulating a primary variable using one or several secondary attributes known exhaustively on the domain. At each node of the grid to be simulated, two conditional distribution functions are inferred. The first one comes from the available conditioning data of the main attribute using, for instance, a multi-Gaussian framework. The
Inverse modeling which transforms obtained geophysical data into physical properties of the Earth... more Inverse modeling which transforms obtained geophysical data into physical properties of the Earth is an essential process for reservoir characterization. We propose a Markov chain Monte Carlo (McMC) workflow consistent with geology, well-logs, seismic data and rock-physics information. The workflow uses Direct Sampling (DS), a multiple-point geostatistical method, for generating realizations from the prior distribution and Iterative Spatial Resampling (ISR)
Second EAGE Integrated Reservoir Modelling Conference, 2014
Second EAGE Integrated Reservoir Modelling Conference, 2014
Water Resources Research, 2014
ABSTRACT We develop a stochastic approach to construct channelized 3D geological models constrain... more ABSTRACT We develop a stochastic approach to construct channelized 3D geological models constrained to borehole measurements as well as geological interpretation. The methodology is based on simple 2D geologist-provided sketches of fluvial depositional elements, which are extruded in the 3rd dimension. Multiple-point geostatistics (MPS) is used to impair horizontal variability to the structures by introducing geometrical transformation parameters. The sketches provided by the geologist are used as elementary training images, whose statistical information is expanded through randomized transformations. We demonstrate the applicability of the approach by applying it to modeling a fluvial valley filling sequence in the Maules Creek catchment, Australia. The facies models are constrained to borehole logs, spatial information borrowed from an analogue and local orientations derived from the present-day stream networks. The connectivity in the 3D facies models is evaluated using statistical measures and transport simulations. Comparison with a statistically equivalent variogram-based model shows that our approach is more suited for building 3D facies models that contain structures specific to the channelized environment and which have a significant influence on the transport processes.