Bottom hole pressure prediction based on hybrid neural networks and Bayesian optimization

Many scholars have focused on applying machine learning models in bottom hole pressure (BHP) prediction. However, the complex and uncertain conditions in deep wells make it difficult to capture spatial and temporal correlations of measurement while drilling (MWD) data with traditional intelligent models. In this work, we develop a novel hybrid neural network, which integrates the Convolution Neural Network (CNN) and the Gate Recurrent Unit (GRU) for predicting BHP fluctuations more accurately. The CNN structure is used to analyze spatial local dependency patterns and the GRU structure is used to discover depth variation trends of MWD data. To further improve the prediction accuracy, we explore two types of GRU-based structure: skip-GRU and attention-GRU, which can capture more long-term potential periodic correlation in drilling data. Then, the different model structures tuned by the Bayesian optimization (BO) algorithm are compared and analyzed. Results indicate that the hybrid models can extract spatial-temporal information of data effectively and predict more accurately than random forests, extreme gradient boosting, back propagation neural network, CNN and GRU. The CNN-attention-GRU model with BO algorithm shows great superiority in prediction accuracy and robustness due to the hybrid network structure and attention mechanism, having the lowest mean absolute percentage error of 0.025%. This study provides a reference for solving the problem of extracting spatial and temporal characteristics and guidance for managed pressure drilling in complex formations.

Intelligent Drilling and Completion:A Review

The application of artificial intelligence(AI)has become inevitable in the petroleum industry.In drilling and completion engineering,AI is regarded as a transformative technology that can lower costs and significantly improve drilling efficiency(DE),In recent years,numerous studies have focused on intelligent algorithms and their application.Advanced technologies,such as digital twins and physics-guided neural networks,are expected to play roles in drilling and completion engineering.However,many challenges remain to be addressed,such as the automatic processing of multi-source and multi-scale data.Additionally,in intelligent drilling and completion,methods for the fusion of data-driven and physicsbased models,few-sample learning,uncertainty modeling,and the interpretability and transferability of intelligent algorithms are research frontiers.Based on intelligent application scenarios,this study comprehensively reviews the research status of intelligent drilling and completion and discusses key research areas in the future.This study aims to enhance the berthing of AI techniques in drilling and completion engineering.

Settling behavior of non-spherical particles in power-law fluids:Experimental study and model development

Solid-particle settling occurs in many natural and industrial processes, such as in the transportation of drilling cuttings and fracturing proppant. Knowledge of the drag coefficient and settling velocity of cuttings and proppant is of significance to hydraulics design, wellbore cleanout, and fracture optimization. We conducted 553 tests to investigate the settling characteristics of spherical and non-spherical particles in power-law fluids. Three major particle shapes (spherical, cubic, and cylindrical) and eight different particle sphericities were used to simulate cuttings and proppant, and power-law fluids were applied to simulate drilling and fracturing fluids. Based on the data analysis, a new drag coefficient-particle Reynolds number correlation was developed to determine the drag coefficient in a power-law fluid for spherical and non-spherical particles. The drag coefficient increases as the sphericity decreases for the same particle Reynolds number. For a specific particle shape, the drag coefficient decreases as the particle Reynolds number increases, but the decreasing trend is reduced at high particle Reynolds number conditions. An explicit settling-velocity equation was proposed to calculate the settling velocity of spherical and non-spherical particles in power-law fluids by considering the effect of sphericity. A suitable range for the proposed model is 0.0001 < Re <200, 0.471 <φ< 1, and 0.505 < n < 1. An illustrative example is presented to show how to calculate the drag coefficient and settling velocity in power-law fluids with given particle and fluid properties.

反应釜的原理、操作、注意事项及应用

反应釜作为一种可进行高温高压化学反应的密闭容器,由于反应范围广、操作简便、反应条件可控等特点,近些年在实验室中迅速普及.相比于常压下的操作,水热/溶剂热反应釜内部的高温高压能够改变物质本身的物理化学性质,实现特定的化学反应,被广泛应用于化学、医药、材料科学等多领域的研究与探索.本综述系统介绍了水热/溶剂热反应釜的结构、基本原理、操作规范以及相关的注意事项,并全面介绍了反应釜在碳纳米材料、无机纳米材料和聚合物材料等研究领域中的重要成果和最新进展.希望本文能够激发科研院校的工作者在安全使用反应釜的前提下创造出更多高质量的成果.

Settling behavior of spherical particles in vertical annulus:Experimental study and model development

Coiled tubing(CT)drilling technology offers significant advantages in terms of cost and efficiency for exploitations of unconventional oil and gas resources.However,the development of CT drilling technol-ogy is restricted by cuttings accumulation in the wellbore due to non-rotation of the drill string and limited circulating capacity.Cuttings cleaning becomes more difficult with the wall resistance of pipe-wellbore annulus on the cutting transport.Accurate description of particle transport process in the pipe-wellbore annulus is,therefore,important for improving the wellbore cleanliness.In this study,high-speed cam-era is used to record and analyze the settling process of particles in the transparent annulus filled with power-law fluids.A total of 540 tests were carried out,involving dimensionless diameters of 0.10-0.95 and particle Reynolds Numbers of 0.01-12.97,revealing the effect of the dimensionless diameter and particle Reynolds number on the annulus wall effect,and the wall factor model with an average relative error of2.75%was established.In addition,a dimensionless parameter,Archimedes number,independent of the settling velocity,was introduced to establish an explicit model of the settling velocity of spherical particles in the vertical annulus,with the average relative error of 7.89%.Finally,a calculation example was provided to show how to use the explicit model of settling velocity in annulus.The results of this study are expected to provide guidance for field engineers to improve the wellbore cleanliness of coiled tubing drilling.

Predicting wall drag coefficient and settling velocity of particle in parallel plates filled with Newtonian fluids

The hindrance of boundary to particle transport exists widely in various industrial applications.In this study,the wall drag force of parallel plates on settling particles was revealed through settling experiment.High-speed camera was used to record and analyze the settling process of particles in parallel plates that are filled with Newtonian fluids.A total of 600 experiments were carried out,involving the range of relative diameter and particle Reynolds number of 0.01-0.95 and 0.004-14.30,respectively.The wall drag coefficient was defined to quantitatively analyze the wall drag force of the parallel plates.The influence of relative diameter,particle properties,rheological properties,and the settling dynamic process on the wall drag coefficient was revealed,and the wall drag coefficient model with mean relative error of 5.90% was established.Furthermore,an explicit settling velocity model with mean relative error of 8.96% for the particle in parallel plates was developed by introducing a dimensionless variable independent of settling velocity,the Archimedes number.Finally,a calculation example was provided to clarify the using process of the explicit model.This research is expected to provide guidance for optimizing water hydraulic fracturing in the oil and gas industry.

Research advances in multi-field coupling model for geothermal reservoir heat extraction

As a kind of clean renewable energy,the production and utilization of geothermal resources can make a great contribution to optimizing the energy structure and energy conservation and emission reduction.The circulating heat extraction process of working fluid will disturb the equilibrium state of physical and chemical fields inside the reservoir,and involve the mutual coupling of heat transfer,flow,stress,and chemical reaction.Revealing the coupling mechanism of flow and heat transfer inside the reservoir during geothermal exploitation can provide important theoretical support for the efficient exploitation of geothermal resources.This paper reviews the research advances of the multi-field coupling model in the reservoir during geothermal production over the past 40 years.The thrust of this paper is on objective analysis and evaluation of the importance of each coupling process and its influence on reservoir heat extraction performance.Finally,we discuss the existing challenges and perspectives to promote the future development of the geothermal reservoir multi-field coupling model.An accurate understanding of the multi-field coupling mechanism,an efficient cross-scale modeling method,as well as the accurate characterization of reservoir fracture morphology,are crucial for the multi-field coupling model of geothermal production.

Carbon dots:An innovative luminescent nanomaterial

In recent years,carbon dots(CDs),including carbon nanodots,carbonized polymer dots,carbon quantum dots,and graphene quantum dots have attracted a mounting interest as readily accessible,nontoxic,and relatively inexpensive carbon-based nanomaterials.Yet,despite intense research for a number of years,a unifying picture is still lacking to clarify the exact definition,clear chemical structure,and unique optical properties of this family of nanomaterials.In this review,we systematically summarize the recent development of CDs from molecular design to related properties of excited states as well as their applications in optoelectronic devices and biology.We point out the current challenges,including exploring precise synthesis,clarifying the structure-property relationship,and regulating singlet and triplet states of fluorescence,phosphorescence,and delayed fluorescence.Moreover,the structural optimization of optoelectronic devices,tumor targeting mechanism,selective imaging,and drug delivery of CDs are also highlighted.We hope that the information provided in this review will inspire more exciting research on CDs from a brand-new perspective and promote practical application of CDs in multiple directions of current and future research.