Aadnoy, B.S., 2010. Modern well design. CRC Press.
Akhlaghi, N., Rezaei, F., 2012. Estimated rate of penetration using artificial neural networks and optimize drilling parameters in directional wells in Ahvaz field. J. Chem. 1, 1–11.
Alum, M.A., Egbon, F., 2011. Semi-Analytical Models on the Effect of Drilling Fluid Properties on Rate of Penetration (ROP). In: Nigeria Annual International Conference and Exhibition. Society of Petroleum Engineers.
Amar, K., Ibrahim, A., 2012. Rate of Penetration Prediction and Optimization using Advances in Artificial Neural Networks, a Comparative Study. Proc. 4th Int. Jt. Conf. Comput. Intell. 647–652.
Anemangely, M., Ramezanzadeh, A., Tokhmechi, B., 2017a. Determination of Constant Coefficients of Bourgoyne and Young drilling rate Model Using a Novel Evolutionary Algorithm. J. Min. Environ.
Anemangely, M., Ramezanzadeh, A., Tokhmechi, B., 2017b. Shear wave travel time estimation from petrophysical logs using ANFIS-PSO algorithm: A case study from Ab-Teymour Oilfield. J. Nat. Gas Sci. Eng. 38, 373–387.
Anemangely, M., Ramezanzadeh, A., Tokhmechi, B., 2017c. Safe Mud Weight Window Determination Using Log Based Methodology. In: 79th EAGE Conference and Exhibition 2017.
Ansari, H.R., Sarbaz Hosseini, M.J., Amirpour, M., 2016. Drilling rate of penetration prediction through committee support vector regression based on imperialist competitive algorithm. Carbonates and Evaporites.
Bahari, A., Baradaran Seyed, A., 2007. Trust-region approach to find constants of Bourgoyne and Young penetration rate model in Khangiran Iranian gas field. In: Latin American & Caribbean Petroleum Engineering Conference. Society of Petroleum Engineers.
Bahari, M.H., Bahari, A., Moradi, H., 2011. Intelligent drilling rate predictor 7, 1511–1519.
Bahari, M.H., Bahari, A., Nejati Moharrami, F., Naghibi Sistani, M.B., 2008. Determining Bourgoyne and Young Model Coefficients Using Genetic Algorithm to Predict Drilling Rate. Appl. Sci. 8, 3050–3054.
Bezminabadi, S.N., Ramezanzadeh, A., Jalali, S.-M.E., Tokhmechi, B., Roustaei, A., 2017. Effect of Rock Properties on Rop Modeling Using Statistical and Intelligent Methods: A Case Study of an Oil Well in Southwest of Iran. Arch. Min. Sci. 62, 131–144.
Black, A.D., Bland, R.G., Curry, D., Ledgerwood, L.W., Robertson, H., Judzis, A., Prasad, U., Grant, T., 2008. Optimization of Deep-Drilling Performance With Improvements in Drill-Bit and Drilling-Fluid Design. In: IADC/SPE Drilling Conference. Society of Petroleum Engineers.
Bourgoyne Jr, A.T., Young Jr, F.S., 1974. A multiple regression approach to optimal drilling and abnormal pressure detection. Soc. Pet. Eng. J. 14, 371–384.
Caicedo, H.U., Calhoun, W.M., Ewy, R.T., 2005. Unique ROP predictor using bit-specific coefficient of sliding friction and mechanical efficiency as a function of confined compressive strength impacts drilling performance. In: SPE/IADC Drilling Conference. Society of Petroleum Engineers.
Gstalder, S., Raynal, J., 2013. Measurement of Some Mechanical Properties of Rocks And Their Relationship to Rock Drillability. J. Pet. Technol. 18, 991–996.
Iqbal, F., 2008. SPE 114543 Drilling Optimization Technique – Using Real Time Parameters. pp. 28–30.
Jing Ning, Fan Honghai, Yinghu, Z., Liu Tianyu, 2013. A New Model of ROP Prediction for Drilling Engineering with Data Mining Technology. Int. J. Adv. Inf. Sci. Serv. Sci. 5, 597–604.
Kahraman, S., Alber, M., 2006. Estimating unconfined compressive strength and elastic modulus of a fault breccia mixture of weak blocks and strong matrix. Int. J. rock Mech. Min. Sci. 43, 1277–1287.
Kelessidis, V.C., 2011. Rock drillability prediction from in situ determined unconfined compressive strength of rock. J. South. African Inst. Min. Metall. 111, 429–436.
Lummus, J.L., Azar, J.J., 1986. Drilling fluids optimization: a practical field approach.
Ma, H., 2011. Formation drillability prediction based on multi-source information fusion. J. Pet. Sci. Eng. 78, 438–446.
Macini, P., Magagni, M., Da Dalt, G., Valente, P., 2007. Bit performance evaluation revisited by means of bit Index and formation drillability catalogue. In: SPE/IADC Middle East Drilling and Technology Conference. Society of Petroleum Engineers.
Macini, P., Magagni, M., Valente, P., 2005. Drill-bit catalog and bit index: a new method for bit performance evaluation. In: SPE Latin American and Caribbean Petroleum Engineering Conference. Society of Petroleum Engineers.
Maldla, E.E., Ohara, S., Campinas, S.U., 1991. Field Verification of Drilling Models and Computerized Selection of Drill Bit , WOB , and Drillslring Rotation 189–195.
Monazami, M., Hashemi, A., Shahbazian, M., 2012. Drilling rate of penetration prediction using artificial neural network: A case study of one of Iranian southern oil fields. J. Oil Gas Bus 6, 21–31.
Moradi, H., Bahari, M.H., Bagher, M., Sistani, N., 2010. Drilling rate prediction using an innovative soft computing approach 5, 1583–1588.
Moraveji, M.K., Naderi, M., 2016. Drilling rate of penetration prediction and optimization using response surface methodology and bat algorithm. J. Nat. Gas Sci. Eng. 31, 829–841.
Nauroy, J.-F., 2011. Geomechanics applied to the petroleum industry. Editions Technip.
Paiaman, A., Al-Askari, M., Salmani, B., 2009. Effect of Drilling Fluid Properties on Rate of Penetration. Nafta 129–134.
Pessier, R.C., Fear, M.J., 1992. Quantifying common drilling problems with mechanical specific energy and a bit-specific coefficient of sliding friction. In: SPE Annual Technical Conference and Exhibition. Society of Petroleum Engineers.
Prasad, U., 2009. Drillability of a Rock in Terms of its Physico-Mechanical and Micro- Structural Properties. 43rd U.S. Rock Mech. Symp. 4th U.S. - Canada Rock Mech. Symp.
Přikryl, R., 2001. Some microstructural aspects of strength variation in rocks. Int. J. Rock Mech. Min. Sci. 38, 671–682.
Rajabioun, R., 2011. Cuckoo optimization algorithm. Appl. Soft Comput. 11, 5508–5518.
Reckmann, H., Jogi, P., Herbig, C., 2007. Using dynamics measurements while drilling to detect lithology changes and to model drilling dynamics. In: ASME 2007 26th International Conference on Offshore Mechanics and Arctic Engineering. American Society of Mechanical Engineers, pp. 915–924.
Rong, L., 2004. Comprehensive Research on Drillability in Drilling Project. Drill. Prod. Technol. 27, 1–3.
Sah, S.L., 2010. Encyclopaedia of petroleum science and engineering. Gyan Publishing House.
Schön, J., 2011. Physical properties of rocks: A workbook. Elsevier.
Seifabad, M.C., Ehteshami, P., 2013. Estimating the drilling rate in Ahvaz oil field. J. Pet. Explor. Prod. Technol. 3, 169–173.
Shi, X., Meng, Y., Li, G., Li, J., Tao, Z., Wei, S., 2015. Confined compressive strength model of rock for drilling optimization. Petroleum 1, 40–45.
Shia, X., Taoa, Z., Menga, Y., Yuana, Y., Jianga, W., Maoa, S., 2016. An Experimental Study of Rock Drillability under Simulated Drilling Conditions. In: International Conference on Geomechanics, Geo-Energy and Geo-Resources.
Singh, T.N., Gupta, A.R., Sain, R., 2006. A comparative analysis of cognitive systems for the prediction of drillability of rocks and wear factor. Geotech. Geol. Eng. 24, 299–312.
Somerton, W., Esfandiari, F., Singhal, A., 1969. Further studies of the relation of physical properties of rock to rock drillability. Society of Petroleum Engineers.
Teale, R., 1965. The concept of specific energy in rock drilling. In: International Journal of Rock Mechanics and Mining Sciences & Geomechanics Abstracts. Elsevier, pp. 57–73.
Thuro, K., Plinninger, R.J., 2003. Hard rock tunnel boring, cutting, drilling and blasting: rock parameters for excavatability. In: 10th ISRM Congress. International Society for Rock Mechanics.
White, C.G., 1969. A rock drillability index. Q. Color. Sch. Mines.
Zhu, H.-Y., Deng, J.-G., Xie, Y.-H., Huang, K.-W., Zhao, J.-Y., Yu, B.-H., 2012. Rock mechanics characteristic of complex formation and faster drilling techniques in Western South China Sea oilfields. Ocean Eng. 44, 33–45.
Zoback, M.D., 2010. Reservoir geomechanics. Cambridge University Press.
)