Drilling Parameter Optimization via Real-Time Energy Analysis

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Solution Overview

Problem

The oil and gas drilling industry faces significant Non-Productive Time (NPT) due to crew competency and mechanical equipment failures, which are costly and inefficient, particularly in determining optimal drilling parameters like Mechanical Specific Energy (MSE) that are susceptible to environmental and geological changes.

Innovation Solution

An automation system for drilling rigs that processes real-time surface and downhole operating parameters to optimize drilling energy, identify learning intervals, calculate drilling energy distributions, and determine target operating parameter values, thereby enhancing drilling efficiency and reducing NPT.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If manual decision-making processes are used for drilling operations, then crew competency and experience can be applied to optimize drilling parameters, but Non-Productive Time (NPT) increases due to human error and operational delays

Engineering Contradiction:

Improvedrilling operation reliabilityVSAvoidNon-Productive Time (NPT)

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The drilling system performs self-optimization by automatically analyzing real-time drilling data, calculating Mechanical Specific Energy (MSE), and adjusting drilling parameters without continuous human intervention. The system serves itself by making real-time decisions based on processed data from sensors and downhole measurements, reducing reliance on manual crew decisions and thereby reducing NPT while maintaining reliability.

Inventive Principle:

Principle #25Self-service

2Productivity

If real-time optimization of drilling parameters is performed manually, then drilling efficiency can be improved, but operational equipment failure rates increase due to human error and delayed responses

Engineering Contradiction:

Improvedrilling efficiencyVSAvoidoperational equipment reliability

Core Design Contradiction:

ProductivityVSReliability

Solution Approach 1:

The system continuously monitors real-time drilling parameters including rate of penetration, weight on bit, rotary speed, and mechanical specific energy. This feedback loop enables the system to detect changes in drilling conditions immediately and automatically adjust parameters to optimize efficiency while preventing equipment failures through real-time anomaly detection and corrective actions.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

Manual mechanical decision-making processes are replaced with an automated computer-based system that processes drilling data and controls drilling parameters. This substitution eliminates human error and delayed responses, improving both drilling efficiency and operational reliability through consistent, data-driven automated control.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Adaptability or versatility

If drilling parameters are optimized based on historical data and crew knowledge, then operational flexibility is maintained, but measurement precision and accuracy of drilling parameter optimization decrease

Engineering Contradiction:

Improveoperational flexibilityVSAvoiddrilling parameter optimization accuracy

Core Design Contradiction:

Adaptability or versatilityVSMeasurement precision

Solution Approach 1:

The system pre-calculates optimal drilling parameters by analyzing historical drilling data and formation characteristics before entering new geological zones. This preliminary action provides accurate baseline parameters that are then refined in real-time, combining the benefits of historical knowledge with precise measurements to maintain both adaptability and measurement accuracy.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system dynamically adjusts drilling parameters based on real-time measurements of mechanical specific energy, rate of penetration, and downhole conditions. This dynamic optimization continuously adapts to changing geological conditions while maintaining high measurement precision through automated data collection and analysis, surpassing the accuracy of manual estimation methods.

Inventive Principle:

Principle #15Dynamics

Data Source

PatentEP3765708B1Drilling parameter optimization for automated well planning, drilling, and guidance systems

Publication Date: 2024.05.08 AI DRILLER INC

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AI summary

An automation system for a drilling rig includes a processor and a computer memory in communication with the processor and storing computer executable instructions, that when implemented by the processor cause the processor to perform functions that include receiving as a function of time at least one of a) at least one surface operating parameter and b) at least one downhole operating parameter. The processor further may at least one of filter and smooth the at least one surface operating parameter and the at least one downhole operating parameter to generate processed data. The processor may generate a measure of drilling energy from the processed data and determine a minimum of the measure of the drilling energy, and calculate a target value of the at least one of the at least one surface operating parameter and the at least one downhole operating parameter.