Travertine Deposit Determination via Stochastic Particle Modeling
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods are ineffective in accurately determining the geological composition of sedimentary basins, particularly the travertine facies, which is crucial for hydrocarbon exploration and exploitation, as they rely on expensive and limited drilling data, and lack a comprehensive modeling approach.
Innovation Solution
A computer-implemented method using a geological gridded model to simulate the trajectory of particles through stochastic movements, updating travertine deposits based on source location relative to water levels and topography, allowing for more accurate estimation of travertine deposits and modeling of carbonate precipitation processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If drilling is performed at different points to determine geological composition, then measurement precision is improved, but loss of time and productivity deteriorate due to multiple drilling operations
Solution Approach 1:
The patent creates a virtual copy of the geological structure through numerical modeling. Instead of physically drilling multiple holes to map the subsurface, the system generates a three-dimensional numerical model that replicates the geological formations, travertine layers, and hydrocarbon deposits. This virtual model can be analyzed repeatedly without additional drilling, thus achieving high measurement precision while maintaining drilling productivity.
Solution Approach 2:
The patent performs preliminary numerical simulations and modeling before actual drilling operations. By pre-calculating the most promising drilling locations and trajectories using the numerical model, the system optimizes the drilling plan in advance. This preliminary action reduces the need for multiple exploratory drills and ensures that each drilling operation is targeted and efficient.
2Loss of substance
If drilling sites are spaced more than a hundred meters apart, then loss of substance is reduced, but measurement precision deteriorates due to limited data points
Solution Approach 1:
The numerical model acts as a continuous virtual representation of the subsurface, filling the gaps between widely spaced drilling points. The model interpolates and extrapolates geological data to create a detailed three-dimensional view of formations, travertine deposits, and hydrocarbon accumulations, maintaining high measurement precision even when physical drill sites are spaced more than 100 meters apart.
Solution Approach 2:
The numerical model serves as an intermediary between the limited physical drilling data points. It processes the sparse data from widely spaced wells and generates a continuous, high-resolution representation of the underground geology. This intermediary model allows for accurate geological interpretation without requiring dense drilling networks.
3Measurement precision
If extensive drilling is performed to map geological structures, then measurement precision is improved, but loss of time and productivity deteriorate
Solution Approach 1:
The patent creates a comprehensive three-dimensional numerical model that serves as a virtual replica of the entire geological structure. This model can be generated and analyzed in silico, allowing for rapid exploration of different scenarios and drilling strategies without the time-consuming process of extensive physical drilling. The numerical model provides complete geological mapping information that would otherwise require numerous drill holes to obtain.
Solution Approach 2:
The patent replaces the mechanical drilling system with a numerical modeling system. Instead of using physical drills to map the subsurface, the system uses computational algorithms to simulate and visualize geological formations. This substitution dramatically reduces the time required for geological mapping, as numerical simulations can be performed much faster than physical drilling operations.
4Device complexity
If existing modeling techniques are used for sedimentary rocks, then device complexity is reduced, but manufacturing precision deteriorates due to ineffective travertine facies modeling
Solution Approach 1:
The patent applies local quality by implementing specific modeling parameters and rules for travertine facies within the broader sedimentary rock model. The numerical model incorporates specialized algorithms that account for the unique characteristics of travertine formation, such as carbonate precipitation processes and deposition patterns. This localized enhancement improves travertine facies determination precision without requiring complete redesign of the entire modeling system.
Solution Approach 2:
The patent introduces specific parameter changes to existing modeling techniques to improve travertine facies modeling. The numerical model incorporates parameters related to carbonate chemistry, water flow dynamics, and deposition rates that are specific to travertine formation. By adjusting and adding these parameters to standard sedimentary rock models, the system achieves high precision in travertine facies determination while maintaining the overall simplicity of the modeling approach.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This method enables efficient and accurate determination of travertine deposits, improving the understanding of geological structures and reducing the need for extensive drilling, while effectively modeling natural travertine formation processes.
Implementation Method 1
determining, in the geological gridded model, a trajectory of a particle introduced at the source cell or at the group of source cells, said trajectory being defined by stochastic movements of the particle
Implementation Method 2
travertine is a continental limestone sedimentary rock, formed by precipitation of carbonates in ground and surface waters, and/or hot sources, according to the following equation: Ca2++2(HCO3−)↔CaCO3+CO2+H2O
Data Source
AI summary
A method for determining a travertine deposit by:receiving a geological gridded model comprising a plurality of cells;receiving a source cell or a group of source cells of the geological gridded model corresponding to a source;determining a trajectory of a particle introduced at the source based on stochastic movements; andupdating a travertine deposit in cells located on the trajectory of the particle.