Pay Zone Prediction Model Using Syntactic Analysis
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Solution Overview
Problem
The current practice of manually analyzing well logs by petrophysicists to identify pay zones in hydrocarbon wells is time-consuming and costly, leading to expensive rig downtime and lost production, especially when multiple wells require evaluation.
Innovation Solution
The development of a pay zone prediction model using well data and syntactic models from existing wells to estimate pay zones in new wells, reducing the need for extensive manual analysis by leveraging computing devices and statistical methods to correlate well and syntactic data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual analysis by petrophysicists is used to identify pay zones, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The patent replaces the manual mechanical analysis process with an automated computer-based system. The computer automatically processes well log data, applies syntactic models, and identifies pay zones without requiring extensive manual review by petrophysicists, thus reducing time loss while maintaining accuracy through algorithmic analysis
Solution Approach 2:
The patent creates syntactic models that replicate and generalize the expertise of petrophysicists. These models capture the essential patterns and relationships from existing well data, allowing the system to make predictions about pay zones in new wells by copying the analytical logic of human experts into a reusable computational framework
2Measurement precision
If manual analysis by petrophysicists is used to identify pay zones, then measurement precision is improved, but loss of energy increases
Solution Approach 1:
The patent substitutes manual human analysis with automated computer processing, eliminating the need for prolonged rig downtime while maintaining analytical precision. The system processes well log data automatically, providing pay zone identification without the energy and cost losses associated with manual review processes
Solution Approach 2:
The patent performs preliminary analysis by creating syntactic models from existing well data before new wells are drilled or before manual review is needed. This pre-computed knowledge base allows rapid prediction of pay zones in new wells without requiring extensive manual analysis, thereby reducing the time and energy losses associated with rig downtime
3Loss of time
If automated prediction model is used to estimate pay zones, then loss of time is reduced, but device complexity increases
Solution Approach 1:
The patent segments the complex prediction task into distinct manageable components: data acquisition module, syntactic model creation module, and pay zone prediction module. Each component handles a specific aspect of the analysis independently, making the overall system more manageable and easier to implement despite the complexity of the prediction task
Solution Approach 2:
The patent introduces syntactic models as intermediary structures that bridge the raw well log data and the final pay zone predictions. These models act as mediators that organize and transform the complex data into useful predictive patterns, simplifying the overall system architecture by breaking down the complex relationship between input data and output predictions into intermediate representation layers
4Measurement precision
If multiple existing wells are reviewed manually, then measurement precision is improved, but productivity decreases
Solution Approach 1:
The patent replaces manual petrophysicist review with automated computer processing that can simultaneously analyze multiple wells. The system processes well log data from multiple existing wells in parallel, maintaining the precision of manual analysis while dramatically increasing the throughput and productivity of well evaluation
Solution Approach 2:
The patent creates a universal prediction system that can handle multiple wells with different characteristics using the same syntactic models. The system is designed to be multi-functional, applying the same analytical framework across diverse well types and formations, thereby maintaining measurement precision while scaling productivity to handle multiple wells simultaneously
Data Source
AI summary
Implementations of pay zone prediction are described. More particularly, apparatus and techniques described herein allow a user to predict pay zones in wells. By accurately predicting pay zones, the user can perforate an existing well at predefined well depths to access hydrocarbon bearing strata while avoiding other undesirable strata (such as water bearing strata). For example, in one possible implementation, well data and syntactic data from a first set of one or more existing wells can be used to create one or more syntactic models. These syntactic models can then be used with water cut and well data from the one or more existing wells to create a pay zone prediction model which can be used with wells outside of the first set of existing wells.