Source Rock Richness Prediction via Wireline and Pyrolysis Data Integration
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Solution Overview
Problem
Traditional methods for evaluating source rock richness, such as pyrolysis, are limited by the number of samples analyzed, making it impossible to assess the source rock potential of unsampled well sections effectively.
Innovation Solution
A method integrating pyrolysis data with inorganic and wireline log datasets to evaluate source rock richness, involving data filtering, cross-checking with sensitive elements, and matching with wireline log data to calculate net source rock thickness and average total organic carbon values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional pyrolysis methods are used to evaluate source rock richness, then the evaluation is based on direct laboratory analysis, but the number of samples that can be analyzed is limited
Solution Approach 1:
The patent creates a predictive model that copies the relationship between pyrolysis data and source rock richness from sampled intervals to unsampled intervals. Wireline log data serves as a surrogate or copy of the physical properties, allowing evaluation of source rock richness without direct pyrolysis analysis of every interval.
Solution Approach 2:
The patent performs preliminary pyrolysis analysis on core samples to establish calibration relationships before applying the model to the entire well. The cross-checked data set from sampled intervals is used in advance to train the predictive model, enabling subsequent rapid evaluation of unsampled intervals.
2Ease of manufacture
If pyrolysis data is used directly without filtering, then the evaluation process is simpler, but unreliable data points and false flags remain in the dataset
Solution Approach 1:
The patent applies filtering and cross-checking procedures in advance to the pyrolysis data from sampled intervals before using it for model calibration. This preliminary data cleaning ensures that only reliable data points are used to establish the predictive relationships, improving the overall reliability of the evaluation.
Solution Approach 2:
The patent implements a feedback mechanism where pyrolysis data is cross-checked against expected ranges and relationships. Data points that fall outside acceptable parameters are identified and removed, creating a self-correcting process that maintains high data quality throughout the evaluation.
3Measurement precision
If only sampled intervals are evaluated, then the evaluation is more accurate, but unsampled well sections cannot be assessed
Solution Approach 1:
The patent uses wireline log data as a surrogate to copy the source rock richness information from sampled intervals to unsampled intervals. The calibrated model transfers the relationships established in sampled intervals to the entire well, including unsampled sections, thereby extending coverage while maintaining accuracy.
Solution Approach 2:
The patent creates a universal evaluation model that can assess source rock richness across all well intervals regardless of sampling status. The integrated approach using multiple data types (pyrolysis, wireline logs) makes the system versatile enough to handle both sampled and unsampled intervals with a single methodology.
Data Source
AI summary
A method to evaluate source rock richness is claimed. The method includes obtaining a source rock sample, collecting pyrolysis data from testing of the sample, filtering the pyrolysis data to produce a filtered pyrolysis data set, extracting a plurality of elements from their respective oxides and cross-checking the filtered pyrolysis data set with the plurality of elements. The method further includes discarding a plurality of unreliable data points from the filtered pyrolysis data set to produce a cross-checked data set, matching the cross-checked data set with wireline log data, determining a minimum value and a maximum value of the wireline log data that are within the cross-checked data set, and collecting depth thicknesses corresponding to the minimum value and the maximum value. The method also includes calculating a sum of the plurality of depth thicknesses, calculating a net source rock thickness, and calculating a corresponding average total organic carbon value.