Comparison of computational intelligence models for cuttings transport in horizontal and deviated wells

Ülker, Erman; Sorgun, Mehmet

doi:10.1016/j.petrol.2016.07.022

Cited by 20 publications

(10 citation statements)

References 27 publications

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“…ML methods use mathematical models to mine nonlinear underlying patterns in data sets, which can help computer systems to predict or classify data . Within the petroleum industry and geosciences, ML models have been used in various applications such as fluid transport analysis, rock typing, reservoir characterization, multiscale imaging of shale source rocks, and phase segmentation of scanning electron microscopy (SEM) images of shale.…”

Section: Introductionmentioning

confidence: 99%

Review of Shale Gas Transport Prediction: Basic Theory, Numerical Simulation, Application of AI Methods, and Perspectives

et al. 2023

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The gas transport mechanism in shale reservoirs is extremely complex and is a typical multiscale and multiphysics coupled transport process, considering the complex shale rock structure, wide distribution of micropores and nanopores in shale gas reservoirs, diverse gas occurrence forms, and large pore size spans. An accurate understanding of the shale gas transport process and mechanism is important for effective exploration of shale gas reservoirs. In this work, a review of the recent progress in the prediction of shale gas transport in porous media is presented. The basic theory of gas transport in nanopores is discussed. The gas transport in organic and inorganic matter and the gas adsorption effect are covered. Then, gas transport simulations with conventional multiscale numerical methods, including molecular dynamics and lattice Boltzmann simulations, are reviewed, and the multiscale modeling methods are discussed. Furthermore, the application of artificial intelligence (AI) methods in shale gas transport research is discussed. The focus is on the characterization of the shale porous geometry, including porosity, tortuosity, pore size distribution, and reconstruction of the shale porous medium. The application of AI-based methods such as neural networks and machine learning for the prediction of porous flow properties is discussed. This study intends to provide a comprehensive review of shale gas transport characteristics and to enable the accessibility of AI tools in the research of shale gas.

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Section: Introductionmentioning

confidence: 99%

Review of Shale Gas Transport Prediction: Basic Theory, Numerical Simulation, Application of AI Methods, and Perspectives

et al. 2023

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“…Inadequate hole cleaning can cause downhole safety accidents, such as pipes becoming stuck, premature bit wear, slow rate of penetration (ROP), formation fracturing, excessive torque and drag on the drillstring, as well as difficulties in logging and cementing. Inadequate removal of drill cuttings is a primary challenge in horizontal well drilling and may increase the cost and risk of drilling while increasing the non-productive time (NPT) [3,[8][9][10][11][12][13][14]. Therefore, it is essential to effectively alleviate inadequate hole cleaning during horizontal well drilling.…”

Section: Introductionmentioning

confidence: 99%

Numerical Simulation of Effective Hole Cleaning by Using an Innovative Elliptical Drillpipe in Horizontal Wellbore

Yan

Sun

2022

Energies

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In the drilling of horizontal wells, the drill cuttings tend to settle down on the low side of the annulus due to gravity and form a stationary bed, which results in hole cleaning problems. In this paper, a novel type of drillpipe with an elliptical shape was proposed to alleviate inadequate hole cleaning during the drilling of horizontal wells. A three-dimensional computational fluid dynamic (CFD) Eulerian-Eulerian approach with the Realizable k-ɛ turbulence model was developed to predict the solid–liquid two-phase flow in the annular space. Numerical examples were given to investigate the influence of different parameters on cuttings’ transport behavior, and the elliptical drillpipe was compared with the circular drillpipe. The annular cuttings concentration, annular pressure drop, and hole cleaning efficiency were evaluated. The numerical results clarify the potential of the elliptical drillpipe to enhance the hole cleaning efficiency without significantly increasing the annular pressure drop. Due to the swirl flow and secondary flow caused by the rotation of the curvature wall, the swaying phenomenon of drill cuttings’ distribution along the rotation direction of drillpipe was observed and enhanced the cuttings transport ability. Using the elliptical drillpipe as a joint-type tool can improve hole cleaning performance. Under the optimum conditions applied in this study, the hole cleaning efficiency increased by nearly 18%.

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“…Some conventional wells are challenged with this process as well as horizontal wells at an inclined position [4,5], posing a threat to reaching the desired depth of drilling. A higher rate of penetration in a wellbore means that the cuttings from the wellbore are lifted mainly because the mud under operation is assisting the drilling bit to cut fresh rock with little exertion of force; this further explains why it is necessary to keep the mud design in an accurate state, suitable for the wellbore and the effective removal of cuttings.…”

Section: Introductionmentioning

confidence: 99%

A CFD Validation Effect of YP/PV from Laboratory-Formulated SBMDIF for Productive Transport Load to the Surface

et al. 2022

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Several technical factors contribute to the flow of cuttings from the wellbore to the surface of the well, some of which are fundamentally due to the speed and inclination of the drill pipe at different positions (concentric and eccentric), the efficacy of the drilling mud considers plastic viscosity (PV) and yield point (YP), the weight of the cuttings, and the deviation of the well. Moreover, these overlaying cutting beds breed destruction in the drilling operation, some of which cause stuck pipes, reducing the rate of rotation and penetration. This current study, while it addresses the apropos of artificial intelligence (AI) with symmetry, employs a three-dimensional computational fluid dynamic (CFD) simulation model to validate an effective synthetic-based mud-drilling and to investigate the potency of the muds’ flow behaviours for transporting cuttings. Furthermore, the study examines the ratio effects of YP/PV to attain the safe transport of cuttings based on the turbulence of solid-particle suspension from the drilling fluid and the cuttings, and its velocity–pressure influence in a vertical well under a concentric and eccentric position of the drilling pipe. The resulting CFD analysis explains that the YP/PV of SBM and OBM, which generated the required capacity to suspend the cuttings to the surface, are symmetric to the experimental results and hence, the position of the drill pipe at the concentric position in vertical wells required a lower rotational speed. A computational study of the synthetic-based mud and its potency of not damaging the wellbore under an eccentric drill pipe position can be further examined.

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Comparison of computational intelligence models for cuttings transport in horizontal and deviated wells

Cited by 20 publications

References 27 publications

Review of Shale Gas Transport Prediction: Basic Theory, Numerical Simulation, Application of AI Methods, and Perspectives

Review of Shale Gas Transport Prediction: Basic Theory, Numerical Simulation, Application of AI Methods, and Perspectives

Numerical Simulation of Effective Hole Cleaning by Using an Innovative Elliptical Drillpipe in Horizontal Wellbore

A CFD Validation Effect of YP/PV from Laboratory-Formulated SBMDIF for Productive Transport Load to the Surface

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