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Slide Drilling Guidance System for Directional Drilling Path Optimization

Authors: Can Pehlivantürk; John D'Angelo; Dingzhou Cao; Dongmei Chen; Pradeepkumar Ashok; Eric Van Oort;

Slide Drilling Guidance System for Directional Drilling Path Optimization

Abstract

Abstract The amount of uncertainty related to directional drilling makes it challenging to accurately model and predict the results of drilling actions, leaving much to human know-how and interpretation. Additionally, few path planning methods in the literature consider the directional steering tool being used which results in a loss of optimality when sliding and rotating instructions are fitted on a geometric optimal path. The formulation of the optimization problem varies greatly between rotary steerable systems (RSS) and mud-motor configurations. Additional cost functions and constraints are present for mud-motor use, which significantly increases the problem complexity. A slide drilling guidance system is proposed to combat this issue and to help automate directional drilling. The guidance system leverages three main modules. The first is a computationally efficient, non-linear wellbore propagation model. The second is a set of cost functions that aims to quantitatively represent the actual value of the well, representing production loss, drilling time, completion cost, and wellbore quality. The last module is a Genetic Algorithm (GA) solver that generates sets of optimal drilling instructions. The guidance system is built into a software package that utilizes an intuitive, easily-accessible Graphical User Interface (GUI) to be an effective advisory tool for the directional driller. The software is currently being implemented into the Real Time Drilling (RTD) system by an operator.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
7
Top 10%
Top 10%
Top 10%
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