Dynamic Infill Well Placement for Changing Reservoir Sweet Spots
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Solution Overview
Problem
Existing methods for placing infill producer wells in hydrocarbon fields are inefficient and prone to human error, requiring extensive manual intervention and time-consuming adjustments due to changing hydrocarbon saturation levels.
Innovation Solution
A computer-implemented system dynamically identifies optimal sweet spots for infill producer wells using simulations and sensors, automatically controlling wellbore drilling machinery in response to trigger events like decreased production flow rates, and continuously monitors and adjusts well placement to enhance hydrocarbon recovery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual methods are used to place infill producer wells, then human intervention allows flexibility in decision-making, but the process becomes time-consuming and prone to human error
Solution Approach 1:
The patent replaces manual mechanical decision-making processes with an automated computer-implemented system that uses sensors, simulations, and algorithms to determine optimal well placement. This substitution eliminates human error and accelerates the well placement adjustment process while maintaining scientific rigor through computational modeling of hydrocarbon saturation levels.
2Adaptability or versatility
If traditional well placement methods are used, then existing infrastructure and procedures can be maintained, but the system cannot efficiently adapt to changing hydrocarbon saturation levels
Solution Approach 1:
The patent implements a dynamic well placement system that continuously monitors hydrocarbon saturation levels through sensors and automatically adjusts infill producer well locations based on real-time data. The system uses simulations to predict optimal well positions as saturation levels change, enabling adaptive response without requiring complete system redesign.
Solution Approach 2:
The system incorporates continuous feedback loops where sensors monitor hydrocarbon saturation levels, the computer system processes this data through simulations, and adjustments are made to well placement based on the results. This feedback mechanism enables the system to adapt to changing reservoir conditions while maintaining controlled complexity through automated decision-making algorithms.
3Productivity
If extensive manual adjustments are made to well placement, then optimal hydrocarbon recovery can be pursued, but computational resources and human effort are excessively consumed
Solution Approach 1:
The patent uses simulations to perform preliminary analysis of optimal well placement positions before actual drilling occurs. By pre-calculating the most effective well locations based on current hydrocarbon saturation levels, the system minimizes the need for extensive computational resources during implementation and reduces human effort in decision-making, while still achieving optimal hydrocarbon recovery.
Data Source
AI summary
In a computer-implemented techniques for dynamic infill producer well placement, a computer system identifies an area of interest in a hydrocarbon field. The area of interest represents a geographical area in which multiple infill producer wells are to be formed to produce hydrocarbons. Within the area of interest, the computer system identifies multiple sweet spot areas. The computer system receives well criteria associated with the multiple infill producer wells and a trigger event to trigger forming the multiple infill producer wells in the multiple sweet spot areas. The computer system determines that the trigger event has occurred. In response, the computer system controls wellbore drilling machinery to form the multiple infill producer wells according to the well criteria in the multiple sweet spot areas.