Christophe Antoine’s research while affiliated with University of Lorraine and other places

Channelized submarine systems are often gathered into complexes and display various stacking patterns. Their internal architectures represent one of the fundamental properties of a reservoir because they impact the connectivity of sand-rich bodies and affect hydrocarbons recovery. Some works have analyzed the static connectivity of various stacking patterns; however, few have qualitatively evaluated the dynamic implications of different stacking patterns on fluid flow circulations. For this reason, we analyze the hydrodynamic responses of several stacking patterns considering a set of many stochastic realizations grouped into three categories, where each category considers one particular stacking pattern setting. To study the hydrodynamic responses, we set a two-phase system containing oil and water, quantify the oil recovery efficiency, the water breakthrough time, and we compute the dissimilarities between the saturation maps at a specific time equal to 0.3 the injected pore volume. The metrics and dissimilarities are then visualized using heat maps and two-dimensional representations based on multidimensional scaling. This approach facilitates the comparison among flow simulations and quantitatively evaluates the differences of stacking patterns in a channelized submarine meandering reservoir. Moreover, our method permits us to estimate the relation between static and dynamic metrics descriptions.

Assisted well correlation aims at complementing sedimentological expertise with computational rigor to increase automation, improve reproducibility and assess uncertainties during stratigraphic correlation. In this work, a computer-assisted method is proposed to automatically generate possible well correlations based on facies interpretation, dipmeter data and prior knowledge about depositional environments. Facies interpretation and dipmeter data may be used to interpolate three-dimensional surfaces using the three-dimensional Bézier cubic curves between pairs of well markers and triangular Bézier cubic patches between triplets of well markers. These curves and surfaces are compared to a theoretical depositional profile generated from depositional environment knowledge by computing the area between the curves and the profile, or the volume between the patches and the profile. The main principle of correlation used in this method assumes that these areas and volumes may be linked to the likelihood of each possible correlation: the higher the area or the volume, the lower the correlation likelihood. Well correlations are computed using correlation costs between all possible marker combinations aggregated by the Dynamic Time Warping Algorithm. The proposed method produces consistent stratigraphic well correlation with respect to the data set. However, this approach is highly sensitive to the well order of correlation because of the Dynamic Time Warping Algorithm.

Computer-assisted stratigraphic correlation can help to produce several scenarios reflecting interpretation uncertainties. In this work, we propose a method which translates sedimentary concepts into a correlation cost for each possible stratigaphic correlation. All these correlation costs are used to populate a cost matrix in order to apply the Dynamic Time Warping algorithm and to compute the n-best correlation sets having the n-least cumulative costs. The proposed cost function reflects prior knowledge about sediment transport direction, and it is tested on two wells penetrating a Middle Jurassic reservoir in the North Sea. Well markers are described by two parameters: (1) the sedimentary facies corresponding to a depositional environment, and (2) the relative distality of the well computed from its position along the sediment transport direction. The main principle of correlation used in this article assumes that a well marker (described by a facies and a distality) cannot be correlated with another well marker described by a depositionally deeper facies at a more proximal position, or a depositionally shallower facies at a more distal position. This approach produces consistent stratigraphic well correlations, and highlights the sensitivity of the solution to the facies zonation and to the relative well distality. Therefore, the proposed rule offers a way to coherently consider chronostratigraphic correlation and the associated uncertainties at the parasequence scale, i.e., at a smaller scale than generally considered in deterministic correlation.

Well-log interpretation and chronostratigraphic well correlation are essential steps in the basin and reservoir modeling, as they provide clues for the quantification of depositional history and flow units. At the sub-seismic scale (1 to 100 meters), correlations affect the layer geometry and the geobodies connectivity but are subject to many uncertainties because of lack of data at the relevant scale. To reduce these uncertainties, several interpretation and correlation steps may be necessary to obtain a model agreed upon by experts, but this process does not assess correlation uncertainties. To reduce correlation bias due to the interpreter and to help assessing stratigraphic uncertainties in a reproducible way, we propose a computer-assisted method which automatically generates possible well correlations based on facies interpretations and formal interpretation concepts. This method uses facies interpretations translated into a paleo-geographic variable inferred from depositional environments (e.g. the position along a proximal-to-distal transect). Assuming that wells have a global distality due to their position with respect to the overall basin geometry during the considered stratigraphic interval, we can interpolate a three-dimensional surface constrained by well-markers and the local stratigraphic dip measurement acquired along wells. These surfaces represent relative paleo-topographic surfaces at a given depositional time. In first approximation, a large paleo-depth gradient should be observed along the sediment transport direction, and a smaller slope should exist along the depositional strike. Well correlations are computed using a correlation cost between all possible marker combinations aggregated by the Dynamic Time Warping algorithm. These correlation costs are based on the shape of the relative paleo-topography. Additionally, proximal facies interpreted in a distal well cannot be associated with distal facies interpreted in a proximal well, and conversely distal facies interpreted in a distal well may be likely associated with a proximal facies interpreted in a proximal well. Along the depositional strike, the method tries to associate identical or close facies with respect to the distality. We apply the developed method to correlate North Sea Jurassic well cores where lagoon, wave-dominated deltaic and fluvial deposits have been identified. Results highlight well-sections where manual biostratigraphic correlations and generated consistent stratigraphic scenarios differ providing interpreters with a map of the most uncertain well sections.

We assess stratigraphic correlation uncertainties by stochastically generating several possible correlations lines between a set of stratigraphic logs. We motivate the use of automatic correlation methods to sample this uncertainty and introduce a stochastic version of Dynamic Time Warping (DTW) that correlates two logs. This method is extended to a larger number of logs using a sequential application of DTW. When available, low-frequency stratigraphic events are correlated first, and then used to constrain the correlation of higher-order events. All DTW variants use elementary correlation costs corresponding to the likelihood of each possible horizon. The method is demonstrated on a carbonate ramp of the Cretaceous southern Provence Basin, SE France, using costs that measure the consistency between the computed platform slope angle and a theoretical depositional profile. We show that these correlation uncertainties significantly impact facies proportions in stratigraphic layers.

In many applications (e.g. object-based simulation), parametric forms are necessary to model geological bodies. In this paper, Non-uniform Rational Basis Splines (NURBS) are used to construct parametric channel forms. The models of geobodies are generated using a small number of parameters, and hence can be easily modified. This can be done by a point and click user interactions for manual editing or by a Monte-Carlo sampling onto parameter statistical distributions for stochastic simulation applications. These channel objects may also serve as support for defining facies regions in a classical reservoir 3D grid and thus for conditioning petrophysical modeling.

Magnetostratigraphy is a powerful tool to provide absolute dating of sediments enabling robust and detailed chronostratigraphic correlations. It is based on the correlation of a magnetic polarity column, observed and measured in a given sediment section, to a magnetic polarity reference scale where polarity changes are well dated via other independent methods. However, magnetostratigraphic correlations are loose as they are only constrained by binary magnetic chrons (i.e. normal or reversal) and their thickness, which are both defined from depth variations of the magnetic remanent directions. The thickness of a given magnetic polarity zone is a function of time and sediment accumulation rate, which may not be stationary, leading to ambiguities when performing the correlations.

Remote sensing data provide significant information to constrain the geometry of geological structures at depth. However, the use of intraformational geomorphologic features such as flatirons and incised valleys often calls for tedious user interaction during 3-D model building. We propose a new method to generate 3-D models of stratigraphic formations, based primarily on remote sensing images and digital elevation models. This method is based on interpretations of the main relief markers and interpolation of a stratigraphic property on a tetahedral mesh covering the domain of study. The tetrahedral mesh provides a convenient way to integrate available data during the interpolation while accounting for discontinuities such as faults. Interpretive expert input may be provided through constrained interactive editing on arbitrary cross-sections, and additional surface or subsurface data may also be integrated in the modeling. We demonstrate this global workflow on a structurally complex basin in the Sierra Madre Oriental, Northeastern Mexico.