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Bit Hydraulics
The Experts below are selected from a list of 108 Experts worldwide ranked by ideXlab platform
Meysam Naderi – One of the best experts on this subject based on the ideXlab platform.

Application of Optimized Least Square Support Vector Machine and Genetic Programming for Accurate Estimation of Drilling Rate of Penetration
International Journal of Energy Optimization and Engineering, 2018CoAuthors: Meysam Naderi, Ehsan KhamehchiAbstract:This article describes how the accurate estimation of the rate of penetration (ROP) is essential to minimize drilling costs. There are various factors influencing ROP such as formation rock, drilling fluid properties, wellbore geometry, type of Bit, Hydraulics, weight on Bit, flow rate and Bit rotation speed. This paper presents two novel methods based on least square support vector machine (LSSVM) and genetic programming (GP). Models are a function of depth, weight on Bit, rotation speed, stand pipe pressure, flow rate, mud weight, Bit rotational hours, plastic viscosity, yield point, 10 second gel strength, 10 minute gel strength, and fluid loss. Results show that LSSVM estimates 92% of field data with average absolute relative error of less than 6%. In addition, sensitivity analysis showed that factors of depth, weight on Bit, stand pipe pressure, flow rate and Bit rotation speed account for 93% of total variation of ROP. Finally, results indicate that LSSVM is superior over GP in terms of average relative error, average absolute relative error, root mean square error, and the coefficient of determination.

drilling rate of penetration prediction and optimization using response surface methodology and bat algorithm
Journal of Natural Gas Science and Engineering, 2016CoAuthors: Mostafa Keshavarz Moraveji, Meysam NaderiAbstract:Abstract Rate of penetration (ROP) prediction is crucial for drilling optimization because of its role in minimizing drilling costs. There are many factors, which determine the drilling rate of penetration. Typical factors include formation properties, mud rheology, weight on Bit, Bit rotation speed, type of Bit, wellbore inclination, and Bit Hydraulics. In this paper, first, the simultaneous effect of six variables on penetration rate using real field drilling data has been investigated. Response surface methodology (RSM) was used to develop a mathematical relation between penetration rate and six factors. The important variables include well depth (D), weight on Bit (WOB), Bit rotation speed (N), Bit jet impact force (IF), yield point to plastic viscosity ratio (Y p /PV), 10 min to 10 s gel strength ratio (10MGS/10SGS). Next, bat algorithm (BA) was used to identify optimal range of factors in order to maximize drilling rate of penetration. Results indicate that the derived statistical model provides an efficient tool for estimation of ROP and determining optimum drilling conditions. Sensitivity study using analysis of variance shows that well depth, yield point to plastic viscosity ratio, weight on Bit, Bit rotation speed, Bit jet impact force, and 10 min to 10 s gel strength ratio have the greatest effect on ROP variation respectively. Cumulative probability distribution of predicted ROP shows that the penetration rate can be estimated accurately at 95% confidence interval. In addition, study shows that by increasing well depth, there is an uncertainty in selecting the jet impact force as the best objective function to determine the effect of Hydraulics on penetration rate.
Oteri, Vincent Akpojevwe – One of the best experts on this subject based on the ideXlab platform.

Drilling optimization : drill Bit performance optimization using DROPS simulator ( Ekofisk/Eldfisk Field)
University of Stavanger Norway, 2010CoAuthors: Oteri, Vincent AkpojevweAbstract:Master’s thesis in Petroleum engineeringTwo drilled Wells: Well A and Well B were analysed under the following input data; drilling
parameter, survey data, lithology data and Bit information using DROPS simulator to showcase
the Bit performance optimization potentials. Apparent Rock Strength Logs (ARSL) were generated
automatically by the simulator for the two drilled wells to give an idea of how hard is the
formatiom and the rate of penetration possible for the Bits.
Interesting plots of the Apparent Rock Strength, Rate of Penetration, Weight on Bit, Revolution
per minute, pump flow rate, Plastic Viscosity, mud Weight and Bit wear versus depth for the Well
A and Well B were expressly presented in this project work.
Appreciable cost per foot savings was made after the Bit performance optimization simulation
have been performed and a much more better savings could have been made if actual figures and
parameters were used rather than assumed.
A better Bit selection was made using ROP, drilling time, Bit wear constant ( automatic evaluation
by DROPS simulatior), Bit cost and cost per foot for selection criteria.
Bit Hydraulics analysis as relevant to cutting removal was adequately explained and evaluated for
each Bit used during the drilling in the Bit performance optimization using the DROPS simulator 
Drilling optimization : drill Bit performance optimization using DROPS simulator ( Ekofisk/Eldfisk Field)
University of Stavanger Norway, 2010CoAuthors: Oteri, Vincent AkpojevweAbstract:Two drilled Wells: Well A and Well B were analysed under the following input data; drilling
parameter, survey data, lithology data and Bit information using DROPS simulator to showcase
the Bit performance optimization potentials. Apparent Rock Strength Logs (ARSL) were generated
automatically by the simulator for the two drilled wells to give an idea of how hard is the
formatiom and the rate of penetration possible for the Bits.
Interesting plots of the Apparent Rock Strength, Rate of Penetration, Weight on Bit, Revolution
per minute, pump flow rate, Plastic Viscosity, mud Weight and Bit wear versus depth for the Well
A and Well B were expressly presented in this project work.
Appreciable cost per foot savings was made after the Bit performance optimization simulation
have been performed and a much more better savings could have been made if actual figures and
parameters were used rather than assumed.
A better Bit selection was made using ROP, drilling time, Bit wear constant ( automatic evaluation
by DROPS simulatior), Bit cost and cost per foot for selection criteria.
Bit Hydraulics analysis as relevant to cutting removal was adequately explained and evaluated for
each Bit used during the drilling in the Bit performance optimization using the DROPS simulator
Mostafa Keshavarz Moraveji – One of the best experts on this subject based on the ideXlab platform.

drilling rate of penetration prediction and optimization using response surface methodology and bat algorithm
Journal of Natural Gas Science and Engineering, 2016CoAuthors: Mostafa Keshavarz Moraveji, Meysam NaderiAbstract:Abstract Rate of penetration (ROP) prediction is crucial for drilling optimization because of its role in minimizing drilling costs. There are many factors, which determine the drilling rate of penetration. Typical factors include formation properties, mud rheology, weight on Bit, Bit rotation speed, type of Bit, wellbore inclination, and Bit Hydraulics. In this paper, first, the simultaneous effect of six variables on penetration rate using real field drilling data has been investigated. Response surface methodology (RSM) was used to develop a mathematical relation between penetration rate and six factors. The important variables include well depth (D), weight on Bit (WOB), Bit rotation speed (N), Bit jet impact force (IF), yield point to plastic viscosity ratio (Y p /PV), 10 min to 10 s gel strength ratio (10MGS/10SGS). Next, bat algorithm (BA) was used to identify optimal range of factors in order to maximize drilling rate of penetration. Results indicate that the derived statistical model provides an efficient tool for estimation of ROP and determining optimum drilling conditions. Sensitivity study using analysis of variance shows that well depth, yield point to plastic viscosity ratio, weight on Bit, Bit rotation speed, Bit jet impact force, and 10 min to 10 s gel strength ratio have the greatest effect on ROP variation respectively. Cumulative probability distribution of predicted ROP shows that the penetration rate can be estimated accurately at 95% confidence interval. In addition, study shows that by increasing well depth, there is an uncertainty in selecting the jet impact force as the best objective function to determine the effect of Hydraulics on penetration rate.