In the traditional well log depth matching tasks,manual adjustments are required,which means significantly labor-intensive for multiple wells,leading to low work efficiency.This paper introduces a multi-agent deep rei...In the traditional well log depth matching tasks,manual adjustments are required,which means significantly labor-intensive for multiple wells,leading to low work efficiency.This paper introduces a multi-agent deep reinforcement learning(MARL)method to automate the depth matching of multi-well logs.This method defines multiple top-down dual sliding windows based on the convolutional neural network(CNN)to extract and capture similar feature sequences on well logs,and it establishes an interaction mechanism between agents and the environment to control the depth matching process.Specifically,the agent selects an action to translate or scale the feature sequence based on the double deep Q-network(DDQN).Through the feedback of the reward signal,it evaluates the effectiveness of each action,aiming to obtain the optimal strategy and improve the accuracy of the matching task.Our experiments show that MARL can automatically perform depth matches for well-logs in multiple wells,and reduce manual intervention.In the application to the oil field,a comparative analysis of dynamic time warping(DTW),deep Q-learning network(DQN),and DDQN methods revealed that the DDQN algorithm,with its dual-network evaluation mechanism,significantly improves performance by identifying and aligning more details in the well log feature sequences,thus achieving higher depth matching accuracy.展开更多
背景与目的:全直肠系膜切除术(TME)是治疗直肠癌的标准术式,与开放TME比较,腹腔镜辅助TME(LaTME)不仅降低了手术创伤,且疗效相当。但对于肥胖、骨盆狭窄、男性低位直肠癌患者,LaTME的盆腔操作仍十分困难,且环周切缘(CRM)阳性的风险增加...背景与目的:全直肠系膜切除术(TME)是治疗直肠癌的标准术式,与开放TME比较,腹腔镜辅助TME(LaTME)不仅降低了手术创伤,且疗效相当。但对于肥胖、骨盆狭窄、男性低位直肠癌患者,LaTME的盆腔操作仍十分困难,且环周切缘(CRM)阳性的风险增加。腹腔镜辅助经肛TME(TaTME)的出现为低位直肠癌切除术提供了一种创新的微创选择,给外科医生提供新的解决方案。本研究比较分析腹腔镜辅助TaTME与LaTME治疗低位直肠癌的临床疗效。方法:回顾性分析广东省中医院胃肠外科2018年7月—2019年1月收治的30例低位直肠癌患者(肿瘤下缘距肛门距离≤5 cm)的临床资料。其中12例行腹腔镜辅助TaTME(TaTME组),18例行LaTME(LaTME组)。比较两组患者的相关临床指标。结果:两组患者在年龄、性别、BMI、ASA分级、肿瘤学分期、肿瘤下缘距肛门距离、肿瘤直径等一般资料均无明显差异(均P>0.05)。两组患者无中转开腹手术,无近期死亡病例。TaTME组较LaTME组手术时间明显缩短(168.5 min vs.239.33 min,P=0.007)、出血量明显减少(66.50 mL vs.160.00 mL,P=0.002)。两组在预防性造口、保肛率、CRM阳性率、淋巴结清扫总数方面差异无统计学意义(均P>0.05)。TaTME组术后住院时间明显短于LaTME组(6.33 d vs.10.83 d,P<0.001)、住院费用明显低于LaTME组(58963元vs.81341元,P<0.001),TaTME组的术后排气时间及恢复全流饮食时间均短于LaTME组,但差异无统计学意义(均P>0.05)。两组术后并发症发生率差异无统计学意义(P>0.05)。结论:腹腔镜辅助TaTME治疗低位直肠癌与LaTME的短期疗效相当,且在某些方面具有一定优势;是安全可行的,值得临床进一步研究和应用。展开更多
基金Supported by the China National Petroleum Corporation Limited-China University of Petroleum(Beijing)Strategic Cooperation Science and Technology Project(ZLZX2020-03).
文摘In the traditional well log depth matching tasks,manual adjustments are required,which means significantly labor-intensive for multiple wells,leading to low work efficiency.This paper introduces a multi-agent deep reinforcement learning(MARL)method to automate the depth matching of multi-well logs.This method defines multiple top-down dual sliding windows based on the convolutional neural network(CNN)to extract and capture similar feature sequences on well logs,and it establishes an interaction mechanism between agents and the environment to control the depth matching process.Specifically,the agent selects an action to translate or scale the feature sequence based on the double deep Q-network(DDQN).Through the feedback of the reward signal,it evaluates the effectiveness of each action,aiming to obtain the optimal strategy and improve the accuracy of the matching task.Our experiments show that MARL can automatically perform depth matches for well-logs in multiple wells,and reduce manual intervention.In the application to the oil field,a comparative analysis of dynamic time warping(DTW),deep Q-learning network(DQN),and DDQN methods revealed that the DDQN algorithm,with its dual-network evaluation mechanism,significantly improves performance by identifying and aligning more details in the well log feature sequences,thus achieving higher depth matching accuracy.
文摘背景与目的:全直肠系膜切除术(TME)是治疗直肠癌的标准术式,与开放TME比较,腹腔镜辅助TME(LaTME)不仅降低了手术创伤,且疗效相当。但对于肥胖、骨盆狭窄、男性低位直肠癌患者,LaTME的盆腔操作仍十分困难,且环周切缘(CRM)阳性的风险增加。腹腔镜辅助经肛TME(TaTME)的出现为低位直肠癌切除术提供了一种创新的微创选择,给外科医生提供新的解决方案。本研究比较分析腹腔镜辅助TaTME与LaTME治疗低位直肠癌的临床疗效。方法:回顾性分析广东省中医院胃肠外科2018年7月—2019年1月收治的30例低位直肠癌患者(肿瘤下缘距肛门距离≤5 cm)的临床资料。其中12例行腹腔镜辅助TaTME(TaTME组),18例行LaTME(LaTME组)。比较两组患者的相关临床指标。结果:两组患者在年龄、性别、BMI、ASA分级、肿瘤学分期、肿瘤下缘距肛门距离、肿瘤直径等一般资料均无明显差异(均P>0.05)。两组患者无中转开腹手术,无近期死亡病例。TaTME组较LaTME组手术时间明显缩短(168.5 min vs.239.33 min,P=0.007)、出血量明显减少(66.50 mL vs.160.00 mL,P=0.002)。两组在预防性造口、保肛率、CRM阳性率、淋巴结清扫总数方面差异无统计学意义(均P>0.05)。TaTME组术后住院时间明显短于LaTME组(6.33 d vs.10.83 d,P<0.001)、住院费用明显低于LaTME组(58963元vs.81341元,P<0.001),TaTME组的术后排气时间及恢复全流饮食时间均短于LaTME组,但差异无统计学意义(均P>0.05)。两组术后并发症发生率差异无统计学意义(P>0.05)。结论:腹腔镜辅助TaTME治疗低位直肠癌与LaTME的短期疗效相当,且在某些方面具有一定优势;是安全可行的,值得临床进一步研究和应用。
