scholarly journals Risk Factors Evaluation for Monitoring of Well Drilling

2021 ◽  
Author(s):  
Shamil Islamov ◽  
Alexey Grigoriev ◽  
Ilya Beloglazov ◽  
Sergey Savchenkov ◽  
Ove Tobias Gudmestad
Keyword(s):  
Anomaly Detection ◽  
Oil And Gas ◽  
New Technologies ◽  
Warning System ◽  
Time Frame ◽  
Gas Production ◽  
Machine Learning Algorithms ◽  
Gradient Boosting ◽  
Drilling Process ◽  
Well Drilling

Drilling of wells for oil and gas production is a highly complex and expensive part of reservoir development. Thus, together with injury prevention, there is a goal to save cost expenditures on downtime and repair of drilling equipment. Nowadays companies have begun to look for ways to improve the efficiency of drilling and minimize non-production time with the help of new technologies. To support decisions in a narrow time frame, it is valuable to have an early warning system. Such a decision support system will help an engineer to intervene in the drilling process and prevent high expenses of unproductive time and equipment repair due to a problem. This work is describing a comparison of machine learning algorithms for anomaly detection during well drilling. Tested models classify drilling problems based on historical data from previously drilled wells. To validate anomaly detection algorithms, we use historical logs of drilling problems for 67 wells at a large brownfield in Siberia, Russia. Wells with problems were selected and analyzed. It should be noted that out of the 67 wells, 20 wells were drilled without expenses for unproductive time. Experiential results illustrated that a model based on gradient boosting can classify the complications in the drilling process best of all.

scholarly journals Research Risk Factors in Monitoring Well Drilling—A Case Study Using Machine Learning Methods

Symmetry ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 1293
Author(s):  
Shamil Islamov ◽  
Alexey Grigoriev ◽  
Ilia Beloglazov ◽  
Sergey Savchenkov ◽  
Ove Tobias Gudmestad
Keyword(s):  
Machine Learning ◽  
Anomaly Detection ◽  
Oil And Gas ◽  
New Technologies ◽  
Learning Algorithms ◽  
Gas Production ◽  
Machine Learning Algorithms ◽  
Gradient Boosting ◽  
Drilling Process ◽  
Well Drilling

This article takes an approach to creating a machine learning model for the oil and gas industry. This task is dedicated to the most up-to-date issues of machine learning and artificial intelligence. One of the goals of this research was to build a model to predict the possible risks arising in the process of drilling wells. Drilling of wells for oil and gas production is a highly complex and expensive part of reservoir development. Thus, together with injury prevention, there is a goal to save cost expenditures on downtime and repair of drilling equipment. Nowadays, companies have begun to look for ways to improve the efficiency of drilling and minimize non-production time with the help of new technologies. To support decisions in a narrow time frame, it is valuable to have an early warning system. Such a decision support system will help an engineer to intervene in the drilling process and prevent high expenses of unproductive time and equipment repair due to a problem. This work describes a comparison of machine learning algorithms for anomaly detection during well drilling. In particular, machine learning algorithms will make it possible to make decisions when determining the geometry of the grid of wells—the nature of the relative position of production and injection wells at the production facility. Development systems are most often subdivided into the following: placement of wells along a symmetric grid, and placement of wells along a non-symmetric grid (mainly in rows). The tested models classify drilling problems based on historical data from previously drilled wells. To validate anomaly detection algorithms, we used historical logs of drilling problems for 67 wells at a large brownfield in Siberia, Russia. Wells with problems were selected and analyzed. It should be noted that out of the 67 wells, 20 wells were drilled without expenses for unproductive time. The experiential results illustrate that a model based on gradient boosting can classify the complications in the drilling process better than other models.

The Use of a Sensor Modules System for Measuring Drilling Parameters in a Bit, Significantly Reduces the Construction Time of Wells in Eastern Siberia

2021 ◽  
Author(s):  
Andrey Alexandrovich Rebrikov ◽  
Anton Anatolyevich Koschenkov ◽  
Anastasiya Gennadievna Rakina ◽  
Igor Dmitrievich Kortunov ◽  
Nikita Vladimirovich Koshelev ◽  
...  
Keyword(s):  
Oil And Gas ◽  
New Technologies ◽  
Field Tests ◽  
Depth Of Cut ◽  
Drilling Process ◽  
Eastern Siberia ◽  
Construction Time ◽  
Stage Of Development ◽  
Drilling Parameters ◽  
Pdc Bit

Abstract Currently, production and exploration drilling has entered a stage of development where one of the highest priority goals is to reduce the time for well construction with new technologies and innovations. One of the key components in this aspect is the utilizing of the latest achievements in the design and manufacture of rock cutting tools – drill bits. This article presents some new ideas on methods for identifying different types of vibrations when drilling with PDC bits using a system of sensors installed directly into the bit itself. In the oil and gas fields of Eastern Siberia, one of the main reasons for ineffective drilling with PDC bits are vibrations, which lead to premature wear of the cutting structure of the bit and the achievement of low ROPs in the dolomite and dolerite intervals. For efficient drilling of wells of various trajectories with a bottom hole assembly (BHA), including a downhole motor (PDM) and a PDC bit, special attention is paid to control of the bit by limiting the depth of cut, as well as the level of vibrations that occur during drilling process. Often, the existing complex of surface and BHA equipment fails to identify vibrations that occur directly on the bit, as well as to establish the true cause of their occurrence. Therefore, as an innovative solution to this problem, a system of sensors installed directly into the bit itself is proposed. The use of such a system makes it possible to determine the drilling parameters, differentiated depending on the lithological properties of rocks, leading to an increase in vibration impact. Together with the Operators, tests have been successfully carried out, which have proven the effectiveness of the application of this technology. The data obtained during the field tests made it possible to determine the type and source of vibration very accurately during drilling. In turn, this made it possible to precisely adjust the drilling parameters according to the drilled rocks, to draw up a detailed road map of effective drilling in a specific interval. Correction of drilling parameters based on the analysis of data obtained from sensors installed in the bit made it possible to reduce the resulting wear of the PDC bit cutting structure and, if necessary, make changes to the bit design to improve the technical and economic indicators. Thus, the use of a system of sensors for measuring the drilling parameters in a bit ensured the dynamic stability of the entire BHA at the bottomhole when drilling in rocks of different hardness, significantly reduced the wear of the drilling tools and qualitatively improved the drilling performance.

scholarly journals ECONOMIC SUPPLY OF INNOVATION TECHNOLOGIES FOR THE DEVELOPMENT OF CARBON HEALTH CARE WITH OIL-WEIGHTED SPARE PARTS

2019 ◽  
pp. 40-52 ◽  
Author(s):  
M. S. Pilka
Keyword(s):  
Oil And Gas ◽  
New Technologies ◽  
Spare Parts ◽  
Hydrodynamic Modeling ◽  
Gas Production ◽  
Information Modeling ◽  
Qualitative Assessment ◽  
Efficient Production ◽  
Investment Efficiency ◽  
Hydrocarbon Reserves

T The possibilities of attraction of investments for efficient removal of hydrocarbon reserves, which belong to hardrecoverable and mechanisms for attracting investments in the further development of oil and gas deposits in Ukraine, are presented. The main principles of the ranking of hydrocarbon reserves are considered, deposits structure analysis is needed to evaluate the prospects of transferring their parts to cost-effective ones if some economic conditions will change, as well as the appearance of new methods and technologies for attracting these reserves into development. For oil and gas companies information about the qualitative characteristics of profitable reserves and their distribution in the collectors is very important. The main advantages of using intelligent oil and gas field technologies, which enable real-time realization of fast processing of large volumes of geological information, modeling of various extraction scenarios, and the adoption of rational management decisions for optimizing oil and gas production are described. Hydrodynamic modeling, as an instrument for the search and growth of hydrocarbon reserves, its quantitative and qualitative assessment and a detailed comprehensive study of productive collectors based on modern achievements in geological and geophysical sciences is one of the main ways of development of hardrecoverable reserves. The application of existing and the creation of new technological solutions for the efficient production of oil and gas with positive economic indicators, is a logical continuation of a complex of works on low-yielding hydrocarbon deposits. The main source of growth of hydrocarbon reserves in deposits with a long history of development are: unidentified reserves outside the productive part of the deposit and missed oil-saturated intervals; oil-saturated intervals in the productive section, which aren’t attracted in the development. The development of hardrecoverable reserves is associated with considerable complexity, but the engineering approach, using development monitoring, hydrodynamic modeling, attracting international experience and new technologies, will increase profitability and obtain additional extraction of significant volumes of hydrocarbons, which will ensure not only the achievement of maximum investment efficiency, but also full usage of natural resources of hydrocarbons.

scholarly journals Learning Representations of Network Traffic Using Deep Neural Networks for Network Anomaly Detection: A Perspective towards Oil and Gas IT Infrastructures

Symmetry ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 1882
Author(s):  
Sheraz Naseer ◽  
Rao Faizan Ali ◽  
P.D.D Dominic ◽  
Yasir Saleem
Keyword(s):  
Anomaly Detection ◽  
Network Traffic ◽  
Oil And Gas ◽  
Resource Planning ◽  
Machine Learning Algorithms ◽  
Data Driven ◽  
Network Data ◽  
It Infrastructure ◽  
Industrial Automation ◽  
Network Anomaly Detection

Oil and Gas organizations are dependent on their IT infrastructure, which is a small part of their industrial automation infrastructure, to function effectively. The oil and gas (O&G) organizations industrial automation infrastructure landscape is complex. To perform focused and effective studies, Industrial systems infrastructure is divided into functional levels by The Instrumentation, Systems and Automation Society (ISA) Standard ANSI/ISA-95:2005. This research focuses on the ISA-95:2005 level-4 IT infrastructure to address network anomaly detection problem for ensuring the security and reliability of Oil and Gas resource planning, process planning and operations management. Anomaly detectors try to recognize patterns of anomalous behaviors from network traffic and their performance is heavily dependent on extraction time and quality of network traffic features or representations used to train the detector. Creating efficient representations from large volumes of network traffic to develop anomaly detection models is a time and resource intensive task. In this study we propose, implement and evaluate use of Deep learning to learn effective Network data representations from raw network traffic to develop data driven anomaly detection systems. Proposed methodology provides an automated and cost effective replacement of feature extraction which is otherwise a time and resource intensive task for developing data driven anomaly detectors. The ISCX-2012 dataset is used to represent ISA-95 level-4 network traffic because the O&G network traffic at this level is not much different than normal internet traffic. We trained four representation learning models using popular deep neural network architectures to extract deep representations from ISCX 2012 traffic flows. A total of sixty anomaly detectors were trained by authors using twelve conventional Machine Learning algorithms to compare the performance of aforementioned deep representations with that of a human-engineered handcrafted network data representation. The comparisons were performed using well known model evaluation parameters. Results showed that deep representations are a promising feature in engineering replacement to develop anomaly detection models for IT infrastructure security. In our future research, we intend to investigate the effectiveness of deep representations, extracted using ISA-95:2005 Level 2-3 traffic comprising of SCADA systems, for anomaly detection in critical O&G systems.

There is no easy solution to Cuba’s fuel challenges

2019 ◽  
Keyword(s):  
United States ◽  
Oil And Gas ◽  
New Technologies ◽  
The United States ◽  
Gas Production ◽  
Oil Price ◽  
Oil And Gas Production ◽  
Content Type ◽  
Generating Capacity ◽  
Major Producer

Subject Cuba's energy troubles. Significance With a previously generous Venezuela facing economic crisis and the United States tightening sanctions, Cuba’s ability to augment its limited domestic oil and gas production is severely constrained. It lacks the export earnings to invest in new technologies and power generating capacity that could ease its fuel supply problems. Russia and China have spoken of offering assistance, but neither is inclined to provide handouts in the absence of commercial returns. Impacts Cuba has tried to trade more with Algeria and Angola but remains vulnerable to international oil price shifts. As a major producer of both sugar and biofuels, Brazil could provide a model for Cuba’s biofuel plans. Cubans are resilient and accustomed to hardship; the country’s looming economic troubles are unlikely to trigger serious unrest.

scholarly journals Expansion of oil and gas production and increase environmental risk

2017 ◽  
pp. 7-16
Author(s):  
V. T. Trofimov ◽  
A. V. Nikolaev ◽  
A. D. Zhigalin ◽  
T. A. Baraboshkina ◽  
M. A. Kharkina ◽  
...  
Keyword(s):  
Oil And Gas ◽  
New Technologies ◽  
National Level ◽  
Oil And Gas Industry ◽  
Gas Production ◽  
Point Of View ◽  
Total Probability ◽  
Hydrocarbon Production ◽  
Marginal Seas ◽  
Emergency Situations

Oil and gas industry shows the danger of this kind of industry, including from the environmental point of view. Entering the waters of marginal seas and ocean significantly aggravated the situation, moving a significant part of the emergency situations related to hydrocarbon production, the level of regional and global. The use of new technologies in the production of shale hydrocarbons added new problems - the total probability of contamination of large amounts of geological space highly toxic chemicals. Tracking down of a new perspective mineral energy source - gas hydrates - allows to plan only while possible passing dangers, but shows, that the ecological risk can many times more. For opposition to threat of occurrence of emergencies in connection with growth of extraction of hydrocarbons expediently creation at a national level of special structures of the control and fast reaction. Such structures can be if necessary opened for the international cooperation, and are entered into jurisdiction of the United Nations Organization.

FACTORS PROVING THE OIL AND GAS POTENTIAL OF TERRIGENOUS RESERVOIRS AT GREAT DEPTHS IN THE BAKU ARCHIPELAGO

2020 ◽  
Vol 10 (5(74)) ◽  
pp. 4-10
Author(s):  
Muhammad Kashif Nawab ◽  
Adalat Hasanov
Keyword(s):  
Grain Size ◽  
Oil And Gas ◽  
Positive Impact ◽  
Sandy Loam ◽  
Size Fraction ◽  
Great Depth ◽  
Gas Production ◽  
Drilling Process ◽  
Exploration Process ◽  
Gas Potential

Baku archipelago is well-known for high oil and gas production even at the great depth due to high sedimentation rate and low compaction during the formation of basin. This paper represent the Garnulomtric analysis of core samples, in which grain size fractions are determined along with porosity of the cores. Four types of rock groups (clayey-aleuritic sand, clayey-sandy aleurolites, sandy-clayey aleurolites and clayey sandy loams) were taken into account. In first group (clayey-aleuritic sand) the dominant grain size fraction is 0.175 mm which lead to increase in porosity, in second group the dominant fractions are 0.055 mm and 0.175 which tend to increase in porosity. In clayey-sandy aleurolites fractions like 0.055 mm and 0.25 mm have negative effect on porosity. Moreover, in clayey-sandy loam deposits, the coarser grains have positive impact on porosity compared to fine grains. On the basis of results obtained, the central part of Baku Archipelago is very promising for oil and gas potential especially the anticlinal zone of Gamamdag, Deniz, Sabail and Nakhchivan.Furthermore, accidents and complications in the drilling process may occur due to incorrect predictions of reservoir and hydrostatic pressure during the exploration process, that’s why, it is highly advisable to take into account this anomalous phenomena when choosing the location of wells.

scholarly journals Estimation of Wellbore and Formation Temperatures during the Drilling Process under Lost Circulation Conditions

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Mou Yang ◽  
Yingfeng Meng ◽  
Gao Li ◽  
Yongjie Li ◽  
Ying Chen ◽  
...  
Keyword(s):  
Heat Exchange ◽  
Oil And Gas ◽  
Exchange Process ◽  
Drilling Process ◽  
Formation Temperature ◽  
Well Drilling ◽  
Lost Circulation ◽  
Deep Well ◽  
Completion Process ◽  
Oil And Gas Resources

Significant change of wellbore and surrounding formation temperatures during the whole drilling process for oil and gas resources often leads by annulus fluid fluxes into formation and may pose a threat to operational security of drilling and completion process. Based on energy exchange mechanisms of wellbore and formation systems during circulation and shut-in stages under lost circulation conditions, a set of partial differential equations were developed to account for the transient heat exchange process between wellbore and formation. A finite difference method was used to solve the transient heat transfer models, which enables the wellbore and formation temperature profiles to be accurately predicted. Moreover, heat exchange generated by heat convection due to circulation losses to the rock surrounding a well was also considered in the mathematical model. The results indicated that the lost circulation zone and the casing programme had significant effects on the temperature distributions of wellbore and formation. The disturbance distance of formation temperature was influenced by circulation and shut-in stages. A comparative perfection theoretical basis for temperature distribution of wellbore-formation system in a deep well drilling was developed in presence of lost circulation.

scholarly journals Sea Ice Management for Oil and Gas Platforms in the Bohai Sea

2017 ◽  
Vol 24 (s2) ◽  
pp. 195-204 ◽  
Author(s):  
Da-yong Zhang ◽  
Song-song Yu ◽  
Yanlin Wang ◽  
Qian-jin Yue
Keyword(s):  
Sea Ice ◽  
Oil And Gas ◽  
Warning System ◽  
Gas Production ◽  
Oil Field ◽  
Security Risks ◽  
Oil And Gas Production ◽  
Safe Production ◽  
Risk Warning ◽  
Main Factor

Abstract Bohai is a typical marginal oil field in an ice region, where most of the oil and gas platforms are economical. Sea ice is the main factor that affects the safety of oil and gas platforms in Bohai. Due to the complexity of the ice load and ice-induced vibrations, there are large security risks when developing Bohai oil and gas in the winter. It is difficult to ensure the safe production of oil and gas in winter using existing sea ice disaster warning technologies. Based on winter oil and gas production in the Bohai Sea’s Liaodong Bay, a set of suitable sea ice management systems is proposed in this paper. These systems integrate sea ice monitoring, risk assessment and risk prediction technologies. Based on the risk warning system, an ice management model of a Bohai ice platform has been put into practice, which ensures the safe production of the platform in winter.

scholarly journals The Prospects of Using the Mechanical Activation Method in the Technological Processes of Oil and Gas Production

2019 ◽  
pp. 76-82
Author(s):  
M. M. Orfanova
Keyword(s):  
Mechanical Activation ◽  
Oil And Gas ◽  
New Technologies ◽  
Gas Production ◽  
Fuel Oil ◽  
Oil Refining ◽  
Cement Stone ◽  
Oil And Gas Production ◽  
Mechanical Loads ◽  
Technological Processes

The need to improve the technological processes of raw fuel resources processing, to search for new technologies and to involve oil and gas waste production wastes as anthropogenic resources becomes urgent. The main directions of using the effects of the mechanical activation of substances in the technological processes of oil and gas production are analyzed.  A brief description of the method of mechanical activation is provided. The prospect of using the method of mechanical activation to solve the problem of waste disposal is shown. The author analyzes the main directions of mechanical activation influence used for changing the composition and properties of hydrocarbons and considers the possibilities of mechanical activation of a substance as an efficient way for accelerating the mechano-chemical processes that occur in hydrocarbons due to intense mechanical loads. The article generalizes the research results concerning the effect of mechanical activation on changes in the physical-chemical properties of oil, fuel oil, bottoms and sludge. The results of using mechanical activation for the preparation of plug-back mixtures based on silica sand and quartziferous waste are summarized. The laboratory research was carried out at a centrifugal-planetary mill. It is established that under the conditions of mechanical activation of hydrocarbons their destruction occurs. The process of transformations is a chain nature. The areas of mechanical and chemical transformations, change of fraction content in residual fuel oil, bottom products, and natural gasoline have been investigated. It has been established that destruction of hydrocarbon fractions takes place. The author demonstrates that processing modes, time and mechanical loads affect the course of hydrocarbon destruction, and its results depend on the type of substance. The researcher proves that it is promising to use the method of mechanical activation to control the properties of mineral flour obtained on the basis of oil sludge. The results of the research indicate clearly that it is possible to get different volume of the light cuts yield by regulating the modes of hydrocarbons processing. The author shows the possibility of increasing the depth of oil refining, as well as the possibility of obtaining a cement mixture with the addition of up to 30% of mechanically activated quartziferous additive without deteriorating the characteristics of cement stone achieved. The method of mechanical activation is promising for the utilization of the wastes of oil and gas complex, as these wastes can be considered the anthropogenic raw materials.

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