A new methodology for optimization and prediction of rate of penetration during drilling operations

2019 ◽  
Vol 36 (2) ◽  
pp. 587-595 ◽  
Author(s):  
Yanru Zhao ◽  
Amin Noorbakhsh ◽  
Mohammadreza Koopialipoor ◽  
Aydin Azizi ◽  
M. M. Tahir
Keyword(s):  
Rate Of Penetration ◽  
Drilling Operations

scholarly journals Prediction of Rate of Penetration for wells at Nam Con Son basin using Artificial Neural Networks models

10.29007/4sdt ◽  
2022 ◽  
Author(s):  
Vu Khanh Phat Ong ◽  
Quang Khanh Do ◽  
Thang Nguyen ◽  
Hoang Long Vo ◽  
Ngoc Anh Thy Nguyen ◽  
...  
Keyword(s):  
Network Model ◽  
Oil And Gas ◽  
Research Approach ◽  
Ann Model ◽  
Rate Of Penetration ◽  
Drilling Parameters ◽  
Drilling Operations ◽  
Ann Models ◽  
Artificial Neural ◽  
Artificial Neural Network Ann

The rate of penetration (ROP) is an important parameter that affects the success of a drilling operation. In this paper, the research approach is based on different artificial neural network (ANN) models to predict ROP for oil and gas wells in Nam Con Son basin. The first is the process of collecting and evaluating drilling parameters as input data of the model. Next is to find the network model capable of predicting ROP most accurately. After that, the study will evaluate the number of input parameters of the network model. The ROP prediction results obtained from different ANN models are also compared with traditional models such as the Bingham model, Bourgoyne & Young model. These results have shown the competitiveness of the ANN model and its high applicability to actual drilling operations.

scholarly journals A New Hybrid Analytical-Machine Learning Method for Real-Time ROP Modeling

2020 ◽  
Vol 11 (1) ◽  
pp. 7589-7604
Keyword(s):  
Machine Learning ◽  
Real Time ◽  
Machine Learning Method ◽  
Learning Method ◽  
Real Time Control ◽  
Rate Of Penetration ◽  
Drilling Operation ◽  
Time Control ◽  
Constant Coefficients ◽  
Drilling Operations

Real-time drilling optimization refers to operations and equipment that could minimize total drilling costs. Drilling speed that is called the rate of penetration (ROP) in the drilling industry can be used as a good indicator for the performance evaluation of the drilling operation. Real-time control for drilling ROP is limited to just a few controllable parameters during drilling operations, that is, WOB, RPM, and hydraulics. These parameters can be controlled from the surface by the driller in real-time. In the traditional methods of ROP modeling, an inflexible equation could be developed between some important effective drilling parameters such as weight on the bit or bit rotational speed and drilling rate of penetration. These models had a low degree of accuracy, and they were not applicable in the newly drilled wells even in the same field with an acceptable degree of accuracy. In this study, a new real-time continues-learning method for ROP modeling was developed. In this method, as the drilling operation gets starts and the drilling data reaches the surface, ROP modeling starts, and as the drilling continues, the model accuracy increases. For the method evaluation, 5 famous existing analytical drilling model was selected. Also, a new ROP model was developed in this work. All of these 6 models contain some constant coefficients that were obtained using a new machine learning method named Rain Optimization Algorithm. In the end, the accuracy of the models was compared. Results show that the presented method for ROP modeling is a very flexible method with a high degree of accuracy that can be easily used in any formation. Also, the newly presented model could increase the accuracy of ROP prediction from 75% to 81%.

APPLICATION OF MUD ANALYSIS LOGGING

Geophysics ◽  
1945 ◽  
Vol 10 (1) ◽  
pp. 76-90
Author(s):  
Robert E. Souther
Keyword(s):  
Oil And Gas ◽  
Drilling Fluid ◽  
Salt Content ◽  
Gas Content ◽  
Drilling Speed ◽  
Drilling Mud ◽  
Local Conditions ◽  
Rate Of Penetration ◽  
High Salt Content ◽  
Drilling Operations

The mud analysis logging system, now widely used for exploratory and routine drilling, continuously analyzes and records the oil and gas content of mud returns from wells being drilled by the rotary method. Oil or gas detected in the returning drilling fluid indicates oil or gas in the formation penetrated by the bit. Results of the continuous analyses are instrumentally correlated to the depths and formations from which the showings originated. A second useful phase of the system plots accurately and in detail rate of penetration or drilling speed on the log as a function of depth. Trucks and trailers provide a mobile housing for all of the mud analysis equipment so that it may be moved rapidly from well to well. Applications of the method may be divided into two classes: 1. Routine drilling in proved areas where it eliminates unnecessary coring, and locates gas caps and completion zones. 2. Exploratory drilling in which it minimizes coring by indicating for testing purposes porous zones containing oil and/or gas. Mud analysis logging can be practiced in areas where the electrical log cannot be used due to high salt content or other local conditions, where dangerous hole conditions make interruption of drilling operations for coring inadvisable, and for evaluating gas zones where cores are difficult to interpret. In addition, each mud analysis logging unit contains equipment to obtain information useful in eliminating washouts, in predicting and preventing blowouts, and in controlling drilling mud characteristics.

scholarly journals New Artificial Neural Networks Model for Predicting Rate of Penetration in Deep Shale Formation

2019 ◽  
Vol 11 (22) ◽  
pp. 6527 ◽  
Author(s):  
Ahmed ◽  
Ali ◽  
Elkatatny ◽  
Abdulraheem
Keyword(s):  
Artificial Intelligence ◽  
Petroleum Industry ◽  
Real Field ◽  
Percentage Error ◽  
Individual Parameter ◽  
Rate Of Penetration ◽  
Drilling Parameters ◽  
Drilling Operations ◽  
Shale Formation ◽  
Artificial Neural

Rate of penetration (ROP) means how fast the drilling bit is drilling through the formations. It is known that in the petroleum industry, most of the well cost is taken by the drilling operations. Therefore, it is very crucial to drill carefully and improve drilling processes. Nevertheless, it is challenging to predict the influence of every single parameter because most of the drilling parameters depend on each other and altering an individual parameter will have an impact on the rest. Due to the complexity of the drilling operations, up to the present time, there is no reliable model that can adequately estimate the ROP. Artificial intelligence (AI) might be capable of building a predictive model from a number of input parameters that correlate to the output parameter. A real field dataset, of shale formation, that contains records of both drilling parameters such as, rotation per minute (RPM), weight on bit (WOB), drilling torque (τ), standpipe pressure (SPP) and flow pump (Q) and mud properties such as, mud weight (MW), funnel and plastic viscosities (FV) (PV), solid (%) and yield point (YP) were used to predict ROP using artificial neural network (ANN). A comparison between the developed ANN-ROP model and the number of selected published ROP models were performed. A novel empirical equation of ROP using the above-mentioned parameters was derived based on ANN technique which is able to estimate ROP with excellent precision (correlation coefficient (R) of 0.996 and average absolute percentage error (AAPE) of 5.776%). The novel ANN-based correlation outperformed three published empirical models and it can be used to predict the ROP without the need for artificial intelligence software.

First Successful Run of 17.5 Inch Hybrid Bit in ADNOC Onshore to Drill Deviated Section

2021 ◽  
Author(s):  
Asif M. Khan ◽  
Frederic Chiodini ◽  
Juma Al Shamsi ◽  
Munir Bashir ◽  
Aseel Mohammed ◽  
...  
Keyword(s):  
Case History ◽  
Service Provider ◽  
Systematic Approach ◽  
Main Element ◽  
Special Design ◽  
Rate Of Penetration ◽  
History Data ◽  
Traditional Design ◽  
Drilling Operations ◽  
Drilling Bit

Abstract In the onshore drilling operation the main objective is always finding ways to optimize cost and improve the efficiency of drilling operations. Among the various available option, one possibility was to drill 17.5" deviated section in one run through the interbedded formation, which cause high vibrations and risk of twist-off. This section previously was drilled with minimum 2-3 bit runs for a heavy casing design. This would definitely reduce the well duration and cost. The plan involved to drill 17.5" deviated section using rotary steerable system using hybrid bit technology. Recent advances in drilling bit design has proved to be very effective in drilling surface hole sections but are limited to drill vertical holes and require multiple runs to complete a section. Special design and cutting structure is required when it comes to drill deviated hole. One supplier has combined the traditional design and come up with hybrid bit structure to achieve this goal of drilling surface deviated hole in one run. This special hybrid bit, drilled successfully 17.5" deviated section in one run with enhanced ROP by 40% compared to previous wells. This saved additional trips to change bit and avoided any stuck pipe and twist off. This kind of strategy has helped to maximize average ROP of 64 ft/hr for the entire section. The main element in optimizing the performance of is the systematic approach towards the bit selection, hydraulics and mud parameters. Outcome of this optimization resulted in case history data which shows that this kind of hybrid bit technology can be used to drill deviated wellbore with better penetration rates, lesser washouts and longer on-bottom time. This technical paper describes the results of first well drilled by a service provider using hybrid bit technology with rotary steerable system in one run. This has resulted in increasing the rate of penetration for the 17.5" deviated top hole section. Applying this kind of hybrid bit technology has not only enhanced the ROP but also helped to save rig days and cost.

Atomic disruption beam theory

2016 ◽  
pp. 3524-3528
Author(s):  
Casey Ray McMahon
Keyword(s):  
Neutron Beam ◽  
Beam Theory ◽  
Solid Material ◽  
Material Matter ◽  
Solid Matter ◽  
Plasma Generation ◽  
Resulting Effect ◽  
Drilling Operations ◽  
The Stability

In this paper, I discuss the theory behind the use of a dense, concentrated neutron particle-based beam. I look at the particle based physics behind such a beam, when it is focused against solid material matter. Although this idea is still only theoretical, it appears that such a beam may be capable of disrupting the stability of the atoms within solid matter- in some cases by passing great volumes of neutrons between the electron and nucleus thus effectively “shielding” the electron from the charge of the nucleus. In other cases, by disrupting the nucleus by firing neutrons into it, disrupting the nucleus and weakening its bond on electrons. In either case- the resulting effect would be a disruption of the atom, which in the case of material matter would cause said material matter to fail, which would appear to the observer as liquification with some plasma generation. Thus, a dense neutron particle based beam could be used to effectively liquefy material matter. Such a beam could bore through rock, metal, or even thick, military grade armour, like that used on tanks- causing such materials to rapidly liquefy. The denser and thicker the neutron beam, the more devastating the effect of the beam- thus the faster material matter will liquefy and the greater the area of liquification. Such a beam would have applications in Defence, mining and drilling operations.

Sign in / Sign up

Export Citation Format

Share Document