Construction of Structurally and Stratigraphically Consistent Structural Models Using the Volume-Based Modelling Technology: Applications to an Australian Dataset

Abstract

This paper describes new techniques and algorithms for building consistent and accurate structural models of the subsurface in structurally and stratigraphically complex areas, and proposes an innovative workflow for iteratively building large-scale models in presence of sparse or noisy data.Contrary to traditional 3D modeling approaches, which consist in modeling first geological interfaces independently from each other before gluing them together to form a watertight representation of geological layers, the proposed technique creates first a 3D unstructured mesh representing the volume of interest, which is then sliced and diced by geological horizons and faults. It is based on a global interpolation method in which a scalar property representing the relative stratigraphic age of the formations is interpolated everywhere in the volume of interest. In the process, the geometry of each horizon is effectively constrained by interpretation data of all other horizons belonging to the same conformable sequence.The interpolation is practically insensitive to the complexity of the fault network (X faults, Y faults, thrusts) and yields a high resolution, 3D representation of geological layers, allowing the extraction of main horizons based on seismic input and of closely spaced intermediate horizon surfaces defined by well data.The proposed technique ensures the preservation of four key quality features:1. Geometrical accuracy: surfaces are as smooth as possible while fitting all input data geometry. 2. Topological correctness: all model contacts are perfect and watertight. 3. Stratigraphic consistency: horizon surfaces cannot cross each other; layering and truncation patterns dictated by the input stratigraphic column are honored everywhere in the model. 4. Structural coherency: variations of fault displacement should be consistent with their size; layer thickness changes should be as regular as possible.These benefits are illustrated through the step-by-step construction and refinement of a large scale geological model located offshore Western Australia. It is also demonstrated that this technique and methodology can successfully be applied to a large variety of structural and stratigraphic contexts.

Implicit Modelling of Geological Structures: A Cartesian Grid Method Handling Discontinuities With Ghost Points

“…where Δ and Δ are the grid spacing in the and axes respectively. As the interpolation functions Φ have the Kronecker delta property (i.e., Φ , ∀ , ∈ ; , ∀ ∈ ), eqns (7), (8), and (9) reduce to a linear combination of the coefficients . We define the combination coefficients δ , δ and δ associated to the nodes ∈ as illustrated on Fig.…”

“…Implicit structural modelling consists in interpreting available field data into a model representing subsurface geological structures [1]- [8]. The model is represented by a scalar function defined on the entire volume of interest; this scalar function is called the implicit function.…”

“…DSI poses this problem as a least square's minimization of both this data regression and a roughness factor, obtaining a unique solution which should be as smooth as possible. In practice, this roughness factor has been designed to minimize the difference between the gradient of the implicit function evaluated on adjacent elements [4], [8], which is dependent on the mesh.…”

“…The roughness factor in DSI is defined as a discrete operator [10]. In practice, this factor may take different forms depending on the chosen domain discretisation scheme [4], [8], [14]. Instead, another approach is to find a continuous operator based on physical arguments, and then discretise it accordingly [13], [15].…”

Building 3D subsurface models conforming to seismic structural and stratigraphic features

“…Naeini and Hale (2015) provide a way to improve this method by using interpreted horizons or unconformities as additional controls to guide the interpolation. Benefiting from recent progresses of high-resolution interpretation of seismic data, Jayr et al (2008), Souche et al (2013Souche et al ( , 2014, Mallet (2014), and Labrunye and Carn (2015) propose volume-based techniques to compute subsurface models. In these methods, densely interpreted seismic horizons, faults, and unconformities are used to build subsurface models conforming to the interpreted structural and stratigraphic framework.…”