Surface-Based Geologic Model Conditioning via Mud Layer Segmentation
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Solution Overview
Problem
Conditioning of surface-based geologic models is challenging, particularly in deepwater sedimentary systems, as traditional methods sacrifice geometry, connectivity, and geologic appearance to honor wireline and seismic data, and modeling mud and channel/lobe configurations simultaneously is difficult due to varying geometries and lack of sufficient information on mud parameters.
Innovation Solution
A computer-implemented method that accesses mud layers in the subsurface, conditions them by emplacing lobes or channels sequentially, and builds a model based on these conditions, using mud trends and proportion trends to define layering and element placement, allowing for more realistic and geologically faithful representations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional cell-based geostatistical methods are used to honor wireline and seismic data, then data consistency is improved, but geometry and connectivity are sacrificed
Solution Approach 1:
The method segments the geologic model into discrete surface-based elements (lobes, channels, mud layers) that can be independently conditioned and positioned. This segmentation allows each element to maintain its geometric integrity while being constrained to honor data, resolving the contradiction between data consistency and geometry preservation
Solution Approach 2:
The invention changes the fundamental parameters of the modeling approach by using functional-form surface representations with explicit geometric definitions rather than cell-based statistical methods. This parameter change enables simultaneous optimization of both data honoring and geometric realism
2Reliability
If traditional cell-based geostatistical methods are used to honor wireline and seismic data, then data consistency is improved, but connectivity is sacrificed
Solution Approach 1:
By segmenting the model into discrete surface-based elements with explicit topological relationships, the method maintains natural connectivity between geologic features while allowing independent conditioning to honor data constraints
Solution Approach 2:
The method performs preliminary conditioning of individual surface elements before final assembly, ensuring that connectivity relationships are established early and maintained throughout the modeling process while data constraints are satisfied
3Shape
If surface-based models are used to maintain geometry, then geometric realism is improved, but conditioning to honor data becomes challenging
Solution Approach 1:
Segmenting the model into discrete surface elements simplifies conditioning by allowing independent adjustment of each element's parameters to honor data, reducing the overall complexity despite maintaining geometric realism
Solution Approach 2:
Preliminary conditioning of individual surface elements with explicit geometric definitions enables systematic data integration without requiring complex simultaneous optimization of the entire model
4Adaptability or versatility
If mud and channel/lobe configurations are modeled simultaneously, then comprehensive representation is improved, but modeling difficulty increases due to varying geometries and insufficient mud parameters
Solution Approach 1:
Segmenting the model into distinct mud layer and channel/lobe elements with separate parameter sets allows comprehensive representation while managing complexity through modular, independent conditioning of each element type
Solution Approach 2:
The method applies local quality by using element-specific parameters and conditioning approaches for mud layers versus channels/lobes, allowing each element type to be modeled with appropriate geometric and physical characteristics without requiring uniform parameters across all features
Data Source
AI summary
A method for conditioning of surface-based geological models is provided. Surface-based geological models seek to represent a portion of the subsurface while honoring the available data. However, conditioning of surface-based geological models may be challenging particularly for situations where the geologic elements, such as lobes or channels, are interspersed with another geological element, such as impermeable mud. To condition the geological model, muds are specified through a mud trend or a set of specified mud layers. For example, each mud layer provides the environment of the geological element, such as the lobe to rest on or the channel to erode into. The surface-based geological model may then be built by sequential conditioning layer by layer, such as bottom upward. In this way, the mud layers provide context in which to place objects during conditioning to better generate the surface-based geological model.