Estimation of acoustic wave pressure and acoustic shear wave from specific energy data using combination wavelet transform with ANFIS-PSO algorithm

سال انتشار: 1395
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 413

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شناسه ملی سند علمی:

NPGC02_195

تاریخ نمایه سازی: 10 تیر 1396

چکیده مقاله:

Throughout the history Petroleum drilling of wells, one of the most important problems of this industry is the lack of speed of drilling deep down. Rock mass or, in other words, the formation intended for drilling, as the drilling environment, plays a very essential role in the drilling speed, depreciation of drilling bit, machines, and overall drilling costs. Acoustic logs role in the process of reservoir characterization is undeniable role. The pressure wave speed and shear wave are used in determining the geo-mechanical parameters and type of formation lithology. In this article using the ANFIS – PSO algorithm, the relationship between rock specific energy with shear wave and pressure wave log is achieved. Using drilling parameters corresponding drilling specific energy (DSE) to formation was calculated. Special energy used as input in the wavelet function, the DSE signal was decomposed to 4th level using a db1 wavelet function. After analysis, wavelet function output used as inputs ANFIS-PSO network. Results have shown that the combination of ANFIS-PSO compared to ANFIS-GA is a higher predicted. So that the corresponding mean square error (MSE) and correlation coefficient to this model were found to be 5.5 and 0.74, pressure wave, 7.7 and 0.68, for shear wave, respectively. The proposed method can provide valuable information on pressure wave speed and shear wave in the absence of petrophysical logs.

نویسندگان

Mohammad Mohammadi Behboud

Graduate Student, School of Mining, Petroleum, and Geophysics Engineering, Shahrood University of Technology

Ahmad Ramezanzadeh

Assistant Professor, School of Mining, Petroleum, and Geophysics Engineering, Shahrood University of Technology

Behzad Tokhmechi

Associate Professor, School of Mining, Petroleum, and Geophysics Engineering, Shahrood University of Technology

Mohammad Anemangely

Ph.D. candidate, School of Mining, Petroleum, and Geophysics Engineering, Shahrood University of Technology