3D Facies Trend Modeling Using Sequence Stratigraphy Constraints
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Solution Overview
Problem
Existing methods for predicting facies distributions in reservoirs are inadequate due to sparse well data, leading to inaccurate 2D trend maps that fail to represent the true geological reality, resulting in poor reservoir property models and loss of predictive power.
Innovation Solution
Incorporating sequence stratigraphy into facies trend modeling by analyzing vertical and lateral relationships of sedimentary rocks, integrating geological data such as sea level changes, sediment supply, and basin subsidence to generate a geologically sound facies trend model that accurately reconstructs the geological history and depositional processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional geostatistical methods are used to predict facies distributions, then the modeling process is simple, but the prediction accuracy is poor due to sparse well data
Solution Approach 1:
The method performs preliminary geological analysis by integrating sequence stratigraphy concepts and depositional environment knowledge before generating facies models. This preliminary action incorporates geological constraints and trends into the modeling framework, allowing the model to predict facies distributions more accurately even with sparse well data by relying on geological principles rather than solely on limited observations
Solution Approach 2:
The method introduces an intermediary layer of geological interpretation between the sparse well data and the final facies model. By using sequence stratigraphy frameworks, depositional environment classifications, and geological trends as intermediaries, the system bridges the gap between limited data and comprehensive reservoir characterization, improving prediction accuracy without requiring dense well coverage
2Reliability
If 2D trend maps are generated from sparse well data, then the process is efficient, but the geological reality is not accurately represented
Solution Approach 1:
The method transitions from traditional 2D trend maps to a three-dimensional facies modeling framework that incorporates vertical stratigraphy and lateral continuity. By adding the vertical dimension and integrating sequence stratigraphy layers, the model captures geological reality more accurately, representing facies distributions through multiple stratigraphic layers rather than single-plane projections, thus improving reliability without excessive time loss
3Loss of information
If facies boundaries are projected vertically onto a plane, then the 2D map creation is simple, but vertical facies variations are lost
Solution Approach 1:
The method implements a nested structure where multiple 2D facies maps representing different stratigraphic layers are stacked vertically to form a 3D facies model. Each layer contains facies information for a specific stratigraphic interval, and these layers are nested within each other to create a comprehensive three-dimensional representation. This nesting approach preserves vertical facies variations while maintaining the simplicity of 2D mapping techniques at each level
Data Source
AI summary
Methods and systems are configured for accessing a three-dimensional (3D) facies model including a set of layers, each layer including boundaries data representing initial facies boundaries for a set of facies represented in that layer; accessing geological constraints data representing facies trends for the set of facies represented in the facies model; for each layer: for each facies type in the layer, determining, for a portion of the layer, a distance from the portion of the layer to a facies boundary for that facies type in the layer; and based on the distance for each facies type and the facies trends represented in the geological constraints data, determining a facies probability value; stacking the layers each including facies probability values for each facies type represented in that layer; simulating facies trends for each facies type; and generating a 3D facies trend model including the simulated facies trends.