Estimation and control for efficient autonomous drilling through layered materials

Spencer, Steven J.; Mazumdar, Anirban; Su, Jiann-Cherng; Foris, Adam; Buerger, Stephen

doi:10.23919/acc.2017.7962950

Cited by 5 publications

(5 citation statements)

References 13 publications

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“…The initial WOB0 used in all the simulations is quite far from the optimal value. Even though the adaptation of the algorithm is faster when further away from the optimum, a more efficient optimization method in this scenario could be a hybrid between the data-driven and physics-based approaches, conceptually similar to what was done by Spencer et al [7]. The information gathered from the initial WOB excitations could be used to roughly tune a physics-based drilling model, and the suggested optimal parameters provided by this model would be the starting point for the ES algorithm which would further home in on the founder point.…”

Section: Discussion Of Resultsmentioning

confidence: 99%

“…A possible remedy for model inaccuracies could be the use of data-driven modelling techniques, or a hybrid between datadriven and physics-based modelling methods. The latter approach was applied by Spencer et al [7] in a study on how to automatically minimize Mechanical Specific Energy (MSE) when drilling through layered materials with a lab-scale rig. A physics-based drilling model was used to find an initial estimate of the optimal WOB.…”

Section: Introductionmentioning

confidence: 99%

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Micro-Testing While Drilling for Rate of Penetration Optimization

Nystad¹,

Павлов²

2021

Preprint

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The Rate of Penetration (ROP) is one of the key parameters related to the efficiency of the drilling process. Within the confines of operational limits, the drilling parameters affecting the ROP should be optimized to drill more efficiently and safely, to reduce the overall cost of constructing the well. In this study, a data-driven optimization method called Extremum Seeking is employed to automatically find and maintain the optimal Weight on Bit (WOB) which maximizes the ROP. To avoid violation of constraints, the algorithm is adjusted with a combination of a predictive and a reactive approach. This method of constraint handling is demonstrated for a maximal limit imposed on the surface torque, but the method is generic and can be applied on various drilling parameters. The proposed optimization scheme has been tested on a high-fidelity drilling simulator. The simulated scenarios show the method's ability to steer the system to the optimum and to handle constraints and noisy data.

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Section: Discussion Of Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Micro-Testing While Drilling for Rate of Penetration Optimization

Nystad¹,

Павлов²

2021

Preprint

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“…It can be noted that the reactive constraint handling method will not make any adjustments to the WOB until the torque limit is exceeded. For this reason, a lower value for T limit than the actual system's limit should be used in Equations ( 17) and (19).…”

Section: Reactive Constraint Handlingmentioning

confidence: 99%

“…The gathered information can then be used to generate recommendations for the driller or for closed loop control by an optimization algorithm [18]. An automated golden search algorithm that varies the WOB to identify drilling with minimal MSE has been tested on a lab-scale drilling rig [19]. Field trials of advisory systems that can suggest variations in the applied WOB and RPM to search for the drilling conditions that yield the lowest MSE have been described in [20,21].…”

Section: Introductionmentioning

confidence: 99%

Real-Time Minimization of Mechanical Specific Energy with Multivariable Extremum Seeking

2021

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Drilling more efficiently and with less non-productive time (NPT) is one of the key enablers to reduce field development costs. In this work, we investigate the application of a data-driven optimization method called extremum seeking (ES) to achieve more efficient and safe drilling through automatic real-time minimization of the mechanical specific energy (MSE). The ES algorithm gathers information about the current downhole conditions by performing small tests with the applied weight on bit (WOB) and drill string rotational rate (RPM) while drilling and automatically implements optimization actions based on the test results. The ES method does not require an a priori model of the drilling process and can thus be applied even in instances when sufficiently accurate drilling models are not available. The proposed algorithm can handle various drilling constraints related to drilling dysfunctions and hardware limitations. The algorithm’s performance is demonstrated by simulations, where the algorithm successfully finds and maintains the optimal WOB and RPM while adhering to drilling constraints in various settings. The simulations show that the ES method is able to track changes in the optimal WOB and RPM corresponding to changes in the drilled formation. As demonstrated in the simulation scenarios, the overall improvements in rate of penetration (ROP) can be up to 20–170%, depending on the initial guess of the optimal WOB and RPM obtained from e.g., a drill-off test or a potentially inaccurate model. The presented algorithm is supplied with specific design choices and tuning considerations that facilitate its simple and efficient use in drilling applications.

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“…Porosity is commonly obtained through physical soil sampling, such as drilling and coring. Although soil samplings provide accurate information, they are expensive and time consuming, especially when the samples need to be in undisturbed condition for porosity determination (Spencer et al 2017). To overcome this problem, many studies have produced equations based on Archie's law for porosity modelling at a minimum cost (e.g.…”

Section: Introductionmentioning

confidence: 99%

An unconventional method for calculating porosity of marine clay deposits using the 2D resistivity method

Rosli

Saad

Rahman

et al. 2020

Near Surface Geophysics

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Various methods were earlier designed to calculate porosity of a formation, but many of them are reliant on physical soil sampling and/or laboratory measurements. The present work examines a recently proposed method, which we call here as Sample-free Porosity Calculation from Resistivity Imaging Data (SPyCRID), to calculate porosity of unconsolidated soils. By conjoining Archie's and Waxman-Smits' equations, SPy-CRID can achieve high accuracy in porosity calculation, while requiring no physical soil-sampling data. Two-dimensional resistivity data acquired at Segantang Garam were modelled to calibrate SPyCRID's workflow and to devise data constraints for marine clay and brackish pore-fluid conditions. Measured porosities from soil samples were used only for calibration and validation purposes. With data transformation added into the workflow, the performance of SPyCRID was improved as it was possible to achieve more precise value for the calculated porosity (error ≤3.1%). The final step to establish SPyCRID's competency was implemented through testing SPy-CRID at the Nibong Tebal test site that has similar geological conditions to the model. Results from this test site showed nominal errors (≤3.9%) in the calculated porosity. SPyCRID could successfully calculate the porosity of the unconsolidated, marine clayey soils with a confidence limit exceeding 96%, while requiring no physical sampling data.

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Estimation and control for efficient autonomous drilling through layered materials

Cited by 5 publications

References 13 publications

Micro-Testing While Drilling for Rate of Penetration Optimization

Micro-Testing While Drilling for Rate of Penetration Optimization

Real-Time Minimization of Mechanical Specific Energy with Multivariable Extremum Seeking

An unconventional method for calculating porosity of marine clay deposits using the 2D resistivity method

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