Tar Mat Prediction via Density Inversion Modeling
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Solution Overview
Problem
Current methods for predicting tar mat formation in hydrocarbon reservoirs are inadequate, as they fail to provide a reliable and quantitative explanation for the occurrence and distribution of tar mats, especially due to late light hydrocarbons charge, which affects fluid properties and density inversions.
Innovation Solution
A method and system that utilize downhole tools and surface/remote equipment to collect data on hydrocarbon reservoirs, estimate molecular sizes of fluid components, and generate density inversion models, combined with gravity current models to predict tar mat formation by analyzing density inversions and fluid migration patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional prediction methods are used for tar mat formation, then the process is simple, but the prediction reliability and accuracy are insufficient
Solution Approach 1:
The patent applies preliminary action by performing reservoir testing and data collection before drilling operations. The system collects fluid property data, compositional data, and density measurements in advance to predict tar mat formation locations and conditions, allowing operators to plan drilling paths that avoid problematic zones beforehand.
Solution Approach 2:
The patent uses density inversion modeling as an intermediary mechanism to connect observed fluid properties with tar mat formation predictions. The system measures fluid density at different depths and uses density inversion analysis to identify conditions favorable for tar mat formation, serving as a bridge between direct measurements and formation predictions.
2Measurement precision
If detailed fluid analysis is performed to improve prediction accuracy, then measurement precision increases, but the time and resources required increase
Solution Approach 1:
The patent applies universality by using a multi-functional reservoir testing system that simultaneously measures multiple fluid properties (density, composition, molecular size) in a single operation. The downhole tool suite performs various measurements during one trip, reducing total time while providing comprehensive data for accurate predictions.
Solution Approach 2:
The patent applies parameter changes by analyzing fluid properties at different depths and conditions to identify trends and thresholds. The system measures density and composition parameters at multiple depth intervals, using changes in these parameters to predict where density inversion and tar mat formation are likely to occur.
3Measurement precision
If comprehensive data collection from multiple sources is implemented, then prediction accuracy improves, but system complexity increases
Solution Approach 1:
The patent applies merging by integrating data from multiple sources (downhole tools, surface equipment, remote equipment) into a unified prediction system. The system combines reservoir testing data, fluid samples, and compositional analysis results into a comprehensive model that predicts tar mat formation, managing complexity through integrated data processing.
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 approach allows for accurate prediction of tar mat formation, providing insights into its occurrence, location, and timing, thereby aiding in avoiding drilling into tar-rich zones and optimizing reservoir management.
Implementation Method 1
the fluid is obtained from the reservoir via operation of a downhole tool disposed in a wellbore
Implementation Method 2
via operation of at least one of the downhole tool, the surface equipment, the remote equipment, and/or a combination thereof, estimating molecular sizes of compositional components of the fluid contained within the reservoir
Implementation Method 3
generating a model of a density inversion of the fluid contained within the reservoir based on the obtained data and the estimated molecular sizes
Data Source
AI summary
A downhole tool, surface equipment, and/or remote equipment are utilized to obtain data associated with a subterranean hydrocarbon reservoir, fluid contained therein, and/or fluid obtained therefrom. At least one condition indicating that a density inversion exists in the fluid contained in the reservoir is identified from the data. Molecular sizes of fluid components contained within the reservoir are estimated from the data. A model of the density inversion is generated based on the data and molecular sizes. The density inversion model is utilized to estimate the density inversion amount and depth and time elapsed since the density inversion began to form within the reservoir. A model of a gravity-induced current of the density inversion is generated based on the data and the density inversion amount, depth, and elapsed time.