会议论文详细信息
11th Curtin University Technology, Science and Engineering (CUTSE) International Conference
Oil well compressive strength analysis from sonic log; a case study
工业技术(总论)
Hamdi, Z.^1 ; Momeni, M.S.^2 ; Meyghani, B.^3 ; Zivar, D.^4 ; Chung, B.Y.^5 ; Bataee, M.^6 ; Asadian, M.A.^7
School of Energy Geoscience Infrastructure and Society, Heriot-Watt University, United Kingdom^1
Department of Petroleum Engineering, Curtin University, Malaysia^2
Department of Mechanical Engineering, Faculty of Engineering Universiti Teknologi PETRONAS, Seri Iskandar
32610, Malaysia^3
Centere of Research in Enhanced Oil Recovery, Universiti Teknologi PETRONAS, Seri Iskandar
32610, Malaysia^4
Department of Chemical Engineering, Universiti Teknologi PETRONAS, Seri Iskandar, Perak Darul Ridzuan
32610, Malaysia^5
School of Engineering, Asia Pacific University of Technology and Innovation, Technology Park, Kuala Lumpur, Malaysia^6
Iranian Offshore Oil Company (IOOC), Khakzad St. Turaj St. Modares Cross, Valiasr St., Tehran, Iran^7
关键词: Drilling performance;    Empirical correlations;    Hard formation;    Physical characteristics;    Rate of penetration;    Rock strength;    Uniaxial compressive strength;    Well logging data;   
Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/495/1/012077/pdf
DOI  :  10.1088/1757-899X/495/1/012077
学科分类:工业工程学
来源: IOP
PDF
【 摘 要 】

Appropriate selection of bits for different bore-hole sections is the key to achieve superior drilling performance. This is done with the intention to maximize the rate of penetration while maintaining bit integrity and drilling safety, which plays an important role in maintaining well economies. An accurate selection of drilling bit is dependent on the physical characteristics of formation and the compressive strength of rocks. The acquisition of rock strength along the wellbore can be obtained from various sources such as logs, cutting and rock mechanical test or drilling data. This paper posed a trial to obtain compressive strength profile of oilfield's formation from a sonic log. According to the results, the formations have been divided into several groups from very soft to very hard formation to optimize bit selection. The acquisition of rock strength information in different conditions is made possible by the generation of similar rock strength logs by different sources. Nevertheless, the best prediction will be given by meter-by-meter based logs from different references. Hence, log based or drilling based methods remains the most preferred methods used to obtain rock strength logs. In this paper, it is desired to predict the compressive strength of wellbore by using empirical correlation based on well logging data and then investigate the confidence of results by data obtained from drilling data. Later, this method is used to predict uniaxial compressive strength in the entire of oilfield.

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