Numerical Optimization for Bottom Hole Assembly Configuration

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Solution Overview

Problem

Conventional methods for determining optimal bottom hole assembly (BHA) configurations are laborious and time-consuming, relying heavily on manual iteration and heuristic experience, making it difficult to find the best configuration among numerous possibilities, and are limited by specific geometric and market restrictions.

Innovation Solution

A numerical optimization technique is employed to automatically generate and evaluate BHA configurations, using a multi-objective optimization process to identify a set of optimal designs by applying BHA design criteria and modeling constraints, and selecting the best configuration based on a cost function, which explores the solution space efficiently and effectively.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If manual iteration and heuristic experience are used to determine optimal BHA configurations, then the process is simple and requires minimal computational resources, but it is laborious, time-consuming, and limited by geometric and market restrictions

Engineering Contradiction:

ImproveBHA configuration design speedVSAvoidTime required for manual iteration

Core Design Contradiction:

ProductivityVSLoss of time

Solution Approach 1:

The patent replaces manual mechanical iteration with a numerical optimization algorithm that automatically evaluates BHA configurations. The system uses computational models to simulate BHA performance under various conditions, substituting the manual trial-and-error process with automated numerical calculations that can rapidly explore the solution space and identify optimal configurations without human intervention.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The patent systematically varies multiple BHA configuration parameters (component types, positions, quantities) within defined ranges and evaluates each configuration using objective functions that model drilling performance. The optimization algorithm changes parameters iteratively to maximize performance metrics while satisfying constraints, enabling rapid exploration of numerous configuration possibilities that would be impractical to evaluate manually.

Inventive Principle:

Principle #35Parameter changes

2Reliability

If numerous BHA configurations are evaluated to find the best design, then the quality of the solution improves, but the computational complexity and time required increase significantly

Engineering Contradiction:

ImproveOptimality of BHA configurationVSAvoidComplexity of optimization process

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent divides the BHA configuration problem into discrete components (drill bit, stabilizers, MWD sensors, telemetry controllers, motors) with specific attributes (type, position, quantity). Each component can be independently selected and positioned, allowing the optimization algorithm to systematically evaluate configurations by combining discrete elements rather than treating the entire BHA as a continuous design space, thereby reducing computational complexity.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent pre-defines design criteria and constraints (geometric restrictions, market limitations, performance requirements) before running the optimization. Objective functions are formulated in advance to evaluate BHA performance, and the solution space is bounded by predefined constraints. This preliminary setup allows the optimization algorithm to focus computational resources only on feasible configurations, reducing the effective search space while maintaining high solution quality.

Inventive Principle:

Principle #10Preliminary action

3Adaptability or versatility

If conventional methods are used, then the process is easy to implement, but it is limited by specific geometric and market restrictions that reduce design flexibility

Engineering Contradiction:

ImproveBHA design flexibilityVSAvoidSimplicity of design process

Core Design Contradiction:

Adaptability or versatilityVSEase of manufacture

Solution Approach 1:

The patent implements a dynamic optimization process that can adapt to different geometric constraints and market conditions by adjusting the objective functions and constraints in the numerical model. The system allows flexible configuration of BHA components (types, positions, quantities) within defined ranges and can re-evaluate configurations as design requirements change, enabling the same framework to handle diverse design scenarios without requiring complete redesign of the optimization process.

Inventive Principle:

Principle #15Dynamics

Data Source

PatentUS20240044238A1Optimal bottom hole assembly configuration

Publication Date: 2024.02.08 BAKER HUGHES OILFIELD OPERATIONS LLC

AI summary

A method of defining a BHA design includes performing a numerical optimization process, which includes applying a bottom hole assembly (BHA) design criterion using a numerical optimization algorithm to identify a set of BHA designs selected from a plurality of possible BHA designs, evaluating multiple objective functions for each BHA design of the set of BHA designs based at least in part on a modeling constraint, and identifying a pareto-front of a solution space of the multiple objective functions using the numerical optimization algorithm. The method also includes selecting a data point from the pareto-front using a cost function, selecting a BHA design from the set of BHA designs using the selected data point, and building a BHA using the selected BHA design to be deployed downhole in a wellbore.