Effect of rock properties on ROP modeling using statistical and intelligent methods: a case study of an oil well in southwest of Iran

• Autorzy: Bezminabadi S. N. , Ramezanzadeh A. , Jalali S. M. E. , Tokhmechi B. , Roustaei A.

Identyfikatory

DOI

10.1515/amsc-2017-0010

Warianty tytułu

PL

Badanie wpływu właściwości skał na prędkość wiercenia przy zastosowaniu metod statystycznych i inteligentnych: studium przypadku: szyb naftowy w południowo-zachodniej części Iranu

• Języki publikacji: EN

Abstrakty

EN

Rate of penetration (ROP) is one of the key indicators of drilling operation performance. The estimation of ROP in drilling engineering is very important in terms of more accurate assessment of drilling time which affects operation costs. Hence, estimation of a ROP model using operational and environmental parameters is crucial. For this purpose, firstly physical and mechanical properties of rock were derived from well logs. Correlation between the pair data were determined to find influential parameters on ROP. A new ROP model has been developed in one of the Azadegan oil field wells in southwest of Iran. The model has been simulated using Multiple Nonlinear Regression (MNR) and Artificial Neural Network (ANN). By adding the rock properties, the estimation of the models were precisely improved. The results of simulation using MNR and ANN methods showed correlation coefficients of 0.62 and 0.87, respectively. It was concluded that the performance of ANN model in ROP prediction is fairly better than MNR method.

PL

Prędkość wiercenia jest jednym z podstawowych parametrów charakteryzujących tempo prac wiertniczych. Oszacowanie prędkości wiercenia jest zagadnieniem kluczowym dla inżynierów wiertnictwa, gdyż pozwala na dokładne określenie czasu trwania prac, a co za tym idzie także kosztów operacyjnych. Szacowanie prędkości wiercenia odbywa się na podstawie modelu uwzględniającego parametry pracy oraz parametry środowiskowe. Pierwszy krok obejmuje pozyskanie danych o fizycznych i mechanicznych właściwościach skał na podstawie profilowania geofizycznego otworu. Zastosowano korelację odpowiednich par danych dla pokreślenie wpływu głównych czynników warunkujących prędkość wiercenia. Nowy model obliczania prędkości wiercenia opracowany został w okręgu naftowym Azadegan w południowo-zachodniej części Iranu. Symulacje prowadzono w oparciu o metodę wielokrotnej regresji nieliniowej a także przy wykorzystaniu sztucznych sieci neuronowych. Poprzez dodanie danych o właściwościach skał, model został znacznie udoskonalony. Wyniki symulacji prowadzonych w oparciu o powyższe metody wykazały współczynniki korelacji na poziomie 0.62 i 0.87. Stwierdzono, że metoda wykorzystująca sztuczne sieci neuronowe daje dokładniejsze szacunki prędkości wiercenia niż podejście bazujące wyłącznie na metodzie obliczania regresji nieliniowej

Słowa kluczowe

EN

ROP; rock properties; MNR; ANN

PL

prędkość wiercenia; właściwości skał; metoda wielokrotnej regresji nieliniowej; sztuczne sieci neuronowe

• Wydawca: Instytut Mechaniki Górotworu PAN
• Czasopismo: Archives of Mining Sciences
• Rocznik: 2017
• Tom: Vol. 62, no. 1
• Strony: 131--144
• Opis fizyczny: Bibliogr. 55 poz., rys., tab., wykr.

Twórcy

autor

Bezminabadi S. N.

• Department of Mining, Petroleum and Geophysics, Shahrood University, Shahrood, Iran

autor

Ramezanzadeh A.

• Department of Mining, Petroleum and Geophysics, Shahrood University, Shahrood, Iran

autor

Jalali S. M. E.

• Department of Mining, Petroleum and Geophysics, Shahrood University, Shahrood, Iran

autor

Tokhmechi B.

• Department of Mining, Petroleum and Geophysics, Shahrood University, Shahrood, Iran

autor

Roustaei A.

• Expert, Petroleum Engineering & Development Company(Pedec), Tehran, Iran

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Uwagi

PL

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017)