New Approaches in ۳D Geomechanical Earth Modeling

Publish Year: 1398
نوع سند: مقاله ژورنالی
زبان: English
View: 111

This Paper With 20 Page And PDF Format Ready To Download

  • Certificate
  • من نویسنده این مقاله هستم

استخراج به نرم افزارهای پژوهشی:

لینک ثابت به این Paper:

شناسه ملی سند علمی:

JR_IRPGA-3-1_004

تاریخ نمایه سازی: 22 شهریور 1401

Abstract:

In this paper two new approaches for building ۳D Geomechanical Earth Model (GEM) were introduced. The first method is a hybrid of geostatistical estimators, Bayesian inference, Markov chain and Monte Carlo, which is called Model Based Geostatistics (MBG). It has utilized to achieve more accurate geomechanical model and condition the model and parameters of variogram. The second approach is the integration of the models resulted of different estimators for more reliable-robust-accurate estimation, and using Ordered Weighted Averaging (OWA) data fusion. More accurate estimations help to achieve better results with less uncertainty in the stage of data fusion. Ordinary Kriging (OK), Universal Kriging (UK), MBG and OWA were utilized for making ۳D GEM of Unconfined Compression Stress (UCS) in a reservoir of an oil field in Dezful Embayment. The results were shown that the accuracy of MBG was twice of UK, whereas the model obtained of OK was unacceptable. The results of OWA were even ۴۰% better than MBG. 

Keywords:

Asmari Reservoir , Geostatistical Estimation with Bayesian Inference , Markov Chain – Monte Carlo , Model Based Geostatistics , Ordered Weighted Averaging , Unconfined Compression Stress

Authors

Behzad Tokhmechi

Associate Professor; Faculty of Mining Eng., Petroleum and Geophysics, Shahrood University of Technology

مراجع و منابع این Paper:

لیست زیر مراجع و منابع استفاده شده در این Paper را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود Paper لینک شده اند :
  • Abdideh M. and Ghasemi A., A comparison of various statistical ...
  • Alexandridis A.K. and Zapranis A.D., Wavelet neural networks: A practical ...
  • Almeida J.A., Use of Geostatistical Models to Improve Reservoir Description ...
  • Al-Zainaldin S. Glover PWJ. and Lorinczi P., Synthetic Fractal Modelling ...
  • Bavand Savadkoohi M. Tokhmechi B. Gloaguen E. Arab Amiri A., ...
  • Brown P.E., ۲۰۱۵, Model-Based Geostatistics the Easy Way, Journal of ...
  • Cao J., Yang J., Wang Y., Wang D., and Shi ...
  • Diggle P.J., Giorgi E., Model-Based Geostatistics for Prevalence Mapping in ...
  • Diggle P.J., Ribeiro P.J., Model Based Geostatistics, Springer Series in ...
  • Deutsch C.V., What in the Reservoir is Geostatistics Good For? ...
  • Fang Y. and Chow T.W.S., Wavelets based neural network for ...
  • Hamada G.M., and Elshafei M.A., Neural Network Prediction of Porosity ...
  • Hewett T.A., Fractal distribution of reservoir heterogeneity and their influence ...
  • Tech. Conf. New Orleans, Louisiana. ۱۹۸۶, SPE ۱۵۳۸۵ ...
  • Hewett T.A., Modelling Reservoir Heterogeneity with Fractals, Quantitative Geology and ...
  • Hsu, H.M., Chen, C.T., Aggregation of fuzzy opinions under group ...
  • Hu L.Y. and Le Ravalec-Dupin M., Elements for an Integrated ...
  • Kamali M.R., Omidvar A., and Kazemzadeh E., ۳D geostatistical modeling ...
  • Karimi A., Moeini F., Shamsoddini-Moghadam M.J., Hosseini S.A., Mohammadi A.H., ...
  • Krainski E.T. Gómez-Rubio V. Bakka H. Lenzi A. Castro-Camilo D. ...
  • Kuncheva L.I., Krishnapuram R., A fuzzy consensus aggregation operator, Fuzzy ...
  • Mariethoz G., When should we use multiple-point geostatistics? Handbook of ...
  • Mariethoz G. and Caers J, Multiple-point geostatistics: stochastic modeling with ...
  • Masoudi P. Memarian H. Aifa T. Tokhmechi B., Geometric Modelling ...
  • Masoudi P. Aifa T. Memarian H. Tokhmechi B., Uncertainty assessment ...
  • Michael H.A., Li H., Boucher A., Sun T., Caers J., ...
  • Ostad M.N., Niri M.E., and Darjani M., ۳D modeling of ...
  • Pyrcz, M.J. and Deutsch, C.V., Geostatistical reservoir modeling, Oxford University ...
  • Rasouli V. Tokhmechi B., Difficulties in using geostatistical models in ...
  • Shiri Y. Tokhmechi B. Zarei Z. Koneshloo M., Self-Affine and ...
  • Soroush H. Rasouli V. Tokhmechi B., A combined Bayesian-Wavelet-Data Fusion ...
  • Souche L. Mahdavi R. Mohammad N.M. Alim S. Masoudi R. ...
  • Tokhmechi B. Memarian H. Ahmadi Noubari H. Moshiri B., A ...
  • Tokhmechi B. Nasiri J. Azizi H. Rabiei M. Rasouli V., ...
  • Tokhmechi B. Rasouli V. Azizi H. Rabiei M., Hybrid Clustering-estimation ...
  • Tyagi A.K. Bastia R. and Das M., Identification and Evaluation ...
  • Tyagi A.K. Guha R. Voleti D. and Sxena K., Challenges ...
  • Yager, R.R., On ordered weighted averaging aggregation operators inmulti criteria ...
  • Yamamoto J.K., On unbiased backtransform of lognormal Kriging estimates, Computer ...
  • Zhang Q. and Beveniste A., Wavelet networks, IEEE Transactions on ...
  • Zhang R. Czado C. and Sigloch K., Bayesian spatial modelling ...
  • نمایش کامل مراجع