نتایج جستجو برای: well drilling

تعداد نتایج: 1533568  

Journal: :journal of artificial intelligence in electrical engineering 0
reza farshbaf zinati department of mechanical engineering, tabriz branch, islamic azad university, tabriz, iran ahmad habibi zad navin department of computer engineering, tabriz branch, islamic azad university, tabriz, iran mohammad reza razfar department of mechanical engineering, amirkabir university of technology, tehran, iran.

the drilling is well known as one of the most common hole making processes in the industry.due to close tolerance requirement for drilled holes in the most of work pieces, onlinecontrolling of the diameter of drilled holes seems to be necessary. in the current work, an onlinedimensional controlling system was developed for drilling process. doing this, drilling processwas executed in different ...

Journal: :Journal of the Japanese Association for Petroleum Technology 1993

Journal: :Journal of the Japanese Association for Petroleum Technology 1993

Journal: :iranian journal of oil & gas science and technology 2012
mostafa sedaghatzadeh abbasali khodadadi mohammad reza tahmasebi birgani

designing drilling fluids for drilling in deep gas reservoirs and geothermal wells is a majorchallenge. cooling drilling fluids and preparing stable mud with high thermal conductivity are ofgreat concern. drilling nanofluids, i.e. a low fraction of carbon nanotube (cnt) well dispersed inmud, may enhance the mixture thermal conductivity compared to the base fluids. thus, they arepotentially usef...

Journal: :REM - International Engineering Journal 2019

Journal: :E3S web of conferences 2023

The design trajectory parameters of 3D horizontal wells in X gas field are not uniform, the construction is random, and lack standardization enough to achieve rapid drilling. Based on analysis data difficulties completed well, according different types, by standardizing drilling tool assembly well design, making full use characteristics formation law, using supporting tools control sand carryin...

Journal: :Applied Intelligence 2022

We present a data-driven and physics-informed algorithm for drilling accident forecasting. The core machine-learning uses the data from telemetry representing time-series. have developed Bag-of-features representation of time series that enables to predict probabilities six types accidents in real-time. model is trained on 125 past 100 different Russian oil gas wells. Validation shows can forec...

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