A Method of Intelligent Scheme Optimization for Non-Stop System Intermittent Production Units

Author:

Wang Cai1,Xiong Chunming1,Shi Junfeng1,Han Qiqing2,Zhang Jianjun1,Zhao Ruidong1,Lei Gang3,Zhang Xishun1,Sun Yizhen1

Affiliation:

1. RIPED CNPC

2. Production Technology Research Institute of Dagang Oilfield Company

3. KFUPM

Abstract

Abstract Long-time and over-frequency system power-off of normal intermittent pumping (NIP) technology may exacerbate wax deposit, hydrodynamic level instability and even system restart failure. As a consequence, non-stop-system intermittent pumping (NSSIP) have been tentatively applied into some wells of low production in the oilfield of Daqing in China. Long time pump stop will reduce well production while frequent pumping will lead to void pumping and high energy consumption. Now, NSSIP production scheme is mostly derived from experience decision, the feed and fetch of pump is unbalanced, and it is doubtful whether the low energy consumption characteristic of NSSIP really works. Thus, it is urgent to carry on the research of intelligent scheme optimization for NSSIP. First, based on the A5 database platform of CNPC, the deliberate non-stop pumping scheme and data acquisition scheme for typical experimental wells will be formulated. Second, data of load, displacement and production rate of pumping wells by NSSIP will be measured in real time, then the pump efficiency vs dynamometer working condition will be calibrated accordingly. The CNN+SNN+HDG model is used for training, and the quantitative diagnosis model of insufficient liquid supply is established to realize the intelligent prediction of pump efficiency through dynamometer recognition. Third, the physical model of bottom hole flowing pressure buildup is established to realize the quantitative evaluation of reservoir liquid supply capacity. Data models for correlation analysis of the pumping time, dynamic liquid level, output rate, system efficiency and other parameters are established. At last, the key parameters that affect the pump balance of feed and fetch and economic benefit of a single well are screened out, and the all above analysis results and models are integrated into the ensemble decision tree model to optimize the most reasonable pumping time and frequency for NSSIP schemes. It is suggested that fluid supply capacity affect the intermittent scheme most. For low permeability and low production well, NSSIP could sustain pump fullness, increase system efficiency and save energy at the same time. Based on the ensemble method for intelligently production scheme optimization, NSSIP could increase system efficiency by 7.8% over normal pumping, and by 4.4% over normal intermittent pumping in average. What's more, NSSIP could reduce energy consumption by 22.14 kWh per day compared with intermittent in average. Non-stop-system intermittent pumping (NSSIP) may effectively prevent pumping system from failures caused by void pumping or long-time system stop. It could also greatly increase pumping and system efficiency and save more energy.

Publisher

SPE

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3