Search · four archives
Search · four archives
19 papers · ranked by Valyu relevance
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…
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…
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…
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…
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…
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…
Ekaterina Gurina, Nikita Klyuchnikov, Ksenia Antipova, Dmitry Koroteev
'Dmitry Koroteev'] Abstract We present a data-driven and physics-informed algorithm for drilling accident forecasting. The core machine-learning algorithm uses the data from the drilling telemetry representing the time-series. We have developed a Bag-offeatures representation of the time series that enables the…
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 A Castello, Thiago Ritto
The bit-rock interaction considerably affects the dynamics of a drill string. One critical condition is the stick-slip oscillations, where torsional vibrations are high; the bit angular speed varies from zero to about two times (or more) the top drive nominal angular speed. In addition, uncertainties should be taken…
Felipe A. Portella, David Buchaca, José Roberto Pereira Rodrigues, Josep Ll. Berral
'Josep Ll. Berral'] Reservoir simulations for petroleum fields and seismic imaging are known as the most demanding workloads for highperformance computing (HPC) in the oil and gas (O&G) industry. The optimization of the simulator numerical parameters plays a vital role as it could save considerable computational…
Nanzhe Wang, Haibin Chang, Xiang-Zhao Kong, Martin O. Saar + 1 more
'Dongxiao Zhang'] aBIC-ESAT, ERE, and SKLTCS, College of Engineering, Peking University, Beijing 100871, P. R. China b Geothermal Energy and Geofluids Group, Department of Earth Sciences, ETH Zürich, 8092, Zürich, Switzerland c School of Energy and Mining Engineering, China University of Mining and Technology…
Máté Mohácsi, Márk Patrik Török, Sára Sáray, Luca Tar + 1 more
Finding optimal parameters for detailed neuronal models is a ubiquitous challenge in neuroscientific research. Recently, manual model tuning has been replaced by automated parameter search using a variety of different tools and methods. However, using most of these software tools and choosing the most appropriate…
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…
Stephan Grein, David R. Penas, Daniel Weindl, Polina Lakrisenko + 2 more
Dynamic models are central to the computational life sciences but typically contain unknown parameters that must be inferred from experimental data. High-throughput measurements have made this task increasingly challenging, yielding high-dimensional search spaces and non-convex objectives with many local optima. This…
Alina Selega, Kieran R. Campbell
Many practical applications require optimization of multiple, computationally expensive, and possibly competing objectives that are well-suited for multi-objective Bayesian optimization (MOBO) procedures. However, for many types of biomedical data, measures of data analysis workflow success are often heuristic and…
Zoe Kutulakos, Patrick Slade
Assistive robotic devices like exoskeletons offer the promise of improving mobility for millions of people. However, developing devices that improve an objective mobility metric is challenging. Human-in-the-loop optimization is a systematic approach for personalizing robotic assistance to maximize a mobility metric…