Kick Risk Forecasting and Evaluating During Drilling Based on Autoregressive Integrated Moving Average Model

Author:

Yin HuORCID,Si MenghanORCID,Li Qian,Zhang Jinke,Dai Liming

Abstract

Timely forecasting of the kick risk after a well kick can reduce the waiting time after well shut-in and provide more time for well killing operations. At present, the multiphase flow model is used to simulate and forecast the pit gain and casing pressure. Due to the complexity of downhole conditions, calculation of the multiphase flow model is difficult. In this paper, the time series analysis method is used to excavate the information contained in the time-varying data of pit gain and casing pressure. A forecasting model based on a time series analysis method of pit gain and casing pressure is established to forecast the pit gain and casing pressure after a kick. To divide the kick risk level and achieve the forecasting of the kick risk before and after well shut-in, kick risk analysis plates based on pit gain and casing pressure are established. Three pit gain cases and one casing pressure case are studied, and a comparison between measured data and predicted data shows that the proposed method has high prediction accuracy and repeatability.

Funder

China National Science and Technology Major Project

China Scholarship Council

Publisher

MDPI AG

Subject

Energy (miscellaneous),Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment,Electrical and Electronic Engineering,Control and Optimization,Engineering (miscellaneous)

Cited by 7 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

1. Study on the Mechanism of Gas Intrusion and Its Transportation in a Wellbore under Shut-in Conditions;Energies;2024-01-03

2. Statistical analysis of past kicks and blowouts occurred in a Middle Eastern oilfield;Journal of Petroleum Exploration and Production Technology;2023-06-17

3. Advances in Well Control: Early Kick Detection and Automated Control Systems;Drilling Engineering and Technology - Recent Advances New Perspectives and Applications;2022-11-23

4. Adoption of deep learning Markov model combined with copula function in portfolio risk measurement;Applied Mathematics and Nonlinear Sciences;2021-12-15

5. Adoption of deep learning Markov model combined with copula function in portfolio risk measurement;Applied Mathematics and Nonlinear Sciences;2021-12-13

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