Development of a new correlation to determine the static Young’s modulus

被引:0
|
作者
Salaheldin Elkatatny
Mohamed Mahmoud
Ibrahim Mohamed
Abdulazeez Abdulraheem
机构
[1] King Fahd University of Petroleum and Minerals,
[2] Advantek Waste Management Services,undefined
关键词
Static Young’s modulus; Dynamic Young’s modulus; Log data; Hydraulic fracturing; In situ stresses; Correlation;
D O I
暂无
中图分类号
学科分类号
摘要
The estimation of the in situ stresses is very crucial in oil and gas industry applications. Prior knowledge of the in situ stresses is essential in the design of hydraulic fracturing operations in conventional and unconventional reservoirs. The fracture propagation and fracture mapping are strong functions of the values and directions of the in situ stresses. Other applications such as drilling require the knowledge of the in situ stresses to avoid the wellbore instability problems. The estimation of the in situ stresses requires the knowledge of the Static Young’s modulus of the rock. Young’s modulus can be determined using expensive techniques by measuring the Young’s modulus on actual cores in the laboratory. The laboratory values are then used to correlate the dynamic values derived from the logs. Several correlations were introduced in the literature, but those correlations were very specific and when applied to different cases they gave very high errors and were limited to relating the dynamic Young’ modulus with the log data. The objective of this paper is to develop an accurate and robust correlation for static Young’s modulus to be estimated directly from log data without the need for core measurements. Multiple regression analysis was performed on actual core and log data using 600 data points to develop the new correlations. The static Young’s modulus was found to be a strong function on three log parameters, namely compressional transit time, shear transit time, and bulk density. The new correlation was tested for different cases with different lithology such as calcite, dolomite, and sandstone. It gave good match to the measured data in the laboratory which indicates the accuracy and robustness of this correlation. In addition, it outperformed all correlations from the literature in predicting the static Young’s modulus. It will also help in saving time as well as cost because only the available log data are used in the prediction.
引用
收藏
页码:17 / 30
页数:13
相关论文
共 50 条
  • [41] A new finite element with variable Young's modulus
    Mazur, Katarzyna
    Krawczuk, Marek
    Dabrowski, Leszek
    INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING, 2023, 39 (07)
  • [42] Young's modulus measurements of human liver and correlation with pathological findings
    Yeh, WC
    Jeng, YM
    Hsu, HC
    Kuo, PL
    Li, ML
    Yang, PM
    Lee, PH
    Li, PC
    2001 IEEE ULTRASONICS SYMPOSIUM PROCEEDINGS, VOLS 1 AND 2, 2001, : 1233 - 1236
  • [43] The Relation between Static Young's Modulus and Dynamic Bulk Modulus of Granular Materials and the Role of Stress History
    Gheibi, Amin
    Hedayat, Ahmadreza
    GEOTECHNICAL EARTHQUAKE ENGINEERING AND SOIL DYNAMICS V: SLOPE STABILITY AND LANDSLIDES, LABORATORY TESTING, AND IN SITU TESTING, 2018, (293): : 373 - 382
  • [44] Optical Measurement of Thermal Vibration Spectra to Determine Young's Modulus of Glass Microfibers
    Chowdhury, Sri Sukanta
    Sherehiy, Andriy
    Jarro, Carlos A.
    Cohn, Robert W.
    2018 IEEE 13TH NANOTECHNOLOGY MATERIALS AND DEVICES CONFERENCE (NMDC), 2018, : 369 - 372
  • [45] Development of beta titanium alloys with low Young's modulus
    Ozaki, T.
    Matsumoto, H.
    Miyazaki, T.
    Hasegawa, M.
    Watanabe, S.
    Hanada, S.
    Medical Device Materials II: Proceedings from the Materials & Processes for Medical Devices Conference 2004, 2005, : 197 - 202
  • [46] A new look into the prediction of static Young's modulus and unconfined compressive strength of carbonate using artificial intelligence tools
    Tariq, Zeeshan
    Abdulraheem, Abdulazeez
    Mahmoud, Mohamed
    Elkatatny, Salaheldin
    Ali, Abdulwahab Z.
    Al-Shehri, Dhafer
    Belayneh, Mandefro W. A.
    PETROLEUM GEOSCIENCE, 2019, 25 (04) : 389 - 399
  • [47] Estimation of the quasi-static Young's modulus of the eardrum using a pressurization technique
    Ghadarghadar, Nastaran
    Agrawal, Sumit K.
    Samani, Abbas
    Ladak, Hanif M.
    COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 2013, 110 (03) : 231 - 239
  • [48] An integrated approach for estimating static Young’s modulus using artificial intelligence tools
    Salaheldin Elkatatny
    Zeeshan Tariq
    Mohamed Mahmoud
    Abdulazeez Abdulraheem
    Ibrahim Mohamed
    Neural Computing and Applications, 2019, 31 : 4123 - 4135
  • [49] Estimation of Static Young's Modulus for Sandstone Formation Using Artificial Neural Networks
    Mahmoud, Ahmed Abdulhamid
    Elkatatny, Salaheldin
    Ali, Abdulwahab
    Moussa, Tamer
    ENERGIES, 2019, 12 (11)
  • [50] Measuring the quasi-static Young's modulus of the eardrum using an indentation technique
    Hesabgar, S. Mohammad
    Marshall, Harry
    Agrawal, Sumit K.
    Samani, Abbas
    Ladak, Hanif M.
    HEARING RESEARCH, 2010, 263 (1-2) : 168 - 176