Search · four archives
Search · four archives
19 papers · ranked by Valyu relevance
Wei Li, Yapeng Liu, Xiang Li, Bowen Deng + 4 more
Optimizing drilling parameters is essential for improving drilling efficiency and reducing operational costs in oil and gas engineering. This study presents an intelligent optimization approach for drilling parameters based on a hydraulic-mechanical specific energy (MSE) model. A time-series data fusion framework…
Li Yang, Zhuohui Lu, Weijian Ren, Tianyi Liu
Parameter Optimization Method Based on the Fireworks Algorithm Authors: ['Li Yang' 'Zhuohui Lu' 'Weijian Ren' 'Tianyi Liu'] The rate of penetration (ROP) is a manifestation of drilling efficiency, and optimizing drilling parameters is an important way to improve it. To achieve a low ROP for a Permian formation in a…
Xiaolan Han, Hailong Wang, Yazhou Feng, Shengdun Zhao + 1 more
'Antonio Riveiro'] To improve chip removal efficiency and drilling performance in oxygen-free copper, a multi-objective optimization of gun drilling process parameters was conducted using a response surface methodology and a genetic algorithm. The Box-Behnken Design (BBD) response surface analysis method was employed…
Linsheng Liu, Yushu Lai, Yiwei Zhang, Lin Huang + 7 more
Carbon fiber reinforced polymer (CFRP) is prone to delamination damage during drilling, which seriously affects the processing quality. This study focuses on the use of variable parameter drilling technology. Firstly, an anisotropic constitutive model and a Hashin failure model for CFRP were constructed. Then, based on…
Jia Ge, Wenchang Zhang, Ming Luo, Giuseppe Catalanotti + 5 more
Carbon-fibre-reinforced-polyetherketonketone (CF/PEKK) has attracted increasing interest in the aviation industry due to its self-healing/recycling properties. However, its machining performance is not well understood and there is a lack of optimization study for minimizing its hole damage and improving the production…
Authors not listed
The global drive towards net-zero has accelerated the adoption of carbon fibre reinforced polymers (CFRP) for lightweight structures in various sectors such as aerospace, automotive, energy and biomedical. Mechanical machining of CFRP is often necessary to meet dimensional or assembly-related requirements. However…
Yonggang Deng, Xiaojing Zhou, Zixuan Feng, Xin Li + 1 more
Introduction Accurately predicting the rate of penetration (ROP) is a critical benchmark for evaluating operational efficiency in drilling operations, and it is necessary to optimize the drilling parameters and construct an accurate ROP prediction model. At present, the correlations between drilling operation…
Yedige Tlegenov, Yoke San Wong, Geok Soon Hong
-In this study, the feed rate optimization model based on a Markov Decision Process (MDP) was introduced for spiral drilling process. Firstly, the experimental data on spiral drilling was taken from literature for different axial force parameters and with various feed rate decisions made, having the length of a hole…
Yuntian Chen, Dongxiao Zhang, Qun Zhao, Dexun Liu
An algorithm named InterOpt for optimizing operational parameters is proposed based on interpretable machine learning, and is demonstrated via optimization of shale gas development. InterOpt consists of three parts: a neural network is used to construct an emulator of the actual drilling and hydraulic fracturing…
Thomas Humphries, Ronald D. Haynes
Optimal well placement and optimal well control are two important areas of study in oilfield development. Although the two problems differ in several respects, both are important considerations in optimizing total oilfield production, and so recent work in the field has considered the problem of addressing both…
Song, Yu, Song, Zehua + 8 more
To address the dual challenge of predicting multiphysics-induced instability and optimizing drilling fluid parameters for openhole wellbores under long-term exposure, a high-fidelity system of coupled governing equations was developed. This system integrates seepage, hydration-induced softening, thermal diffusion, and…
Li Chen
Through the research and development of the regression prediction function of support vector machine, this paper applies it to the prediction of drilling fluid performance parameters and the formulation design of drilling fluid. The research in this paper can reduce the experimental workload and improve the efficiency…
Daniel Svensson, Rickard Sjögren, David Sundell, Andreas Sjödin + 1 more
Selecting the proper parameter settings for bioinformatic software tools is challenging. Not only will each parameter have an individual effect on the outcome, but there are also potential interaction effects between parameters. Both of these effects may be difficult to predict. To make the situation even more complex…
Viktor Duplyakov, Anton Morozov, Dmitriy Popkov, Egor Shel + 4 more
'Albert Vainshtein' 'Evgeny Burnaev' 'Andrei Osiptsov' 'Grigory Paderin'] We describe a stacked model for predicting the cumulative fluid production for an oil well with a multistage-fracture completion based on a combination of Ridge Regression and CatBoost algorithms. The model is developed based on an extended…
Américo Cunha, Christian Soize, Rubens Sampaio
This work intends to analyze the nonlinear stochastic dynamics of drillstrings in horizontal configuration. For this purpose, it considers a beam theory, with effects of rotatory inertia and shear deformation, which is capable of reproducing the large displacements that the beam undergoes. The friction and shock…
Riley Hickman, Matteo Aldeghi, Alán Aspuru-Guzik
Model-based optimization strategies, such as Bayesian optimization (BO), have been deployed across the natural sciences in design and discovery campaigns due to their sample efficiency and flexibility. The combination of such strategies with automated laboratory equipment and/or high-performance computing in a…
Alejandro F. Villaverde, Fabian Fröhlich, Daniel Weindl, Jan Hasenauer + 1 more
Mechanistic kinetic models usually contain unknown parameters, which need to be estimated by optimizing the fit of the model to experimental data. This task can be computationally challenging due to the presence of local optima and ill-conditioning. While a variety of optimization methods have been suggested to…
Riley Hickman, Priyansh Parakh, Austin Cheng, Qianxiang Ai + 3 more
Experiment planning algorithms are a required component of autonomous platforms for scientific discovery. Selecting a suitable optimization algorithm for a novel application is an important yet difficult choice a researcher has to make based on past empirical performance on similar tasks. To facilitate the evaluation…
Vigneshbabu Thangarathinam, Devapriya Chattopadhyay
Predation is one of the driving forces that shaped the marine ecosystems through time. Apart from the anti-predatory strategies adopted by the prey, the predatory outcome is often indirectly influenced by the other members of the ecological community. Association between organisms are often found to influence the…