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Abstract

With the development of science and technology, in the field of oilfield commissioning, the requirements for process management are more and more standardized and scientific, and the requirements for decentralized equipment status detection and maintenance are also higher and higher. It is the hope of any manager to eliminate hidden dangers and prevent them in a timely manner. This paper introduces an intelligent debugging model based on big data. Based on the big data mechanism, the model is divided into different functions according to different functions and requirements. It can ensure the authenticity of debugging data, coordinate all big data work through the big data communication mechanism, and conduct scientific management of debugging data. The model is divided into three levels: data acquisition layer, data transmission layer and control management layer. The offshore oil intelligent debugging platform software based on big data technology is built. A new intelligent debugging method for offshore oil based on big data is presented to study the warning information, fault location and equipment health status of intelligent debugging. Development for Marine oil intelligent debugging applications, for business people to provide intelligent Marine oil intelligent debugging method, provide data support for management decision-making, implementation of the lean management data in the field of intelligent debugging, improving the capacity of intelligent debugging data analysis and mining, effective use of the existing intelligent debugging automation system and other related data in the system, solved the “huge amounts of data, information, the lack of a” awkward situation, improve intelligence debugging application function, meet the demand of intelligent debugging of each department, improve the efficiency of debugging and running reliability and intelligent management.

Keywords

Intelligent debugging offshore oil big data communication mechanism

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References

Yun

and Wenxue

, Strategies of Chinese Offshore Oil Engineering Companies to Go Global[J], China Oil & Gas 22(88.4) (2015), 17–22.

Son

B.Y.

, Lee

E.B.

and Using

Energies.

, Text Mining to Estimate Schedule Delay Risk of 13 Offshore Oil and Gas EPC Case Studies During the Bidding Process[J], Energies 12(10) (2019), 1956–1962.

Pedersen

, Durdevic

and Yang

, Review of Slug Detection, Modeling and Control Techniques for Offshore Oil & Gas Production Processes[J], IFAC Papers On Line 48(6) (2015), 89–96.

Serrano

X.M.

, Baums

I.B.

and Smith

T.B.

, Long distance dispersal and vertical gene flow in the Caribbean brooding coral Porites astreoides[J], Entific Reports 6(1) (2016), 21619–21626.

Hardisty

P.E.

, Michaela

and Cooper

K.E.

, The role of marine science in managing environmental risk offshore[J], The APPEA Journal 58(2) (2018), 562–571.

Ferguson

, Oil and gas companies need to adapt to attract digital natives[J], Offshore 78(2) (2018), 64–64.

Hawkins

A.D.

, Pembroke

A.E.

and Popper

A.N.

, Information gaps in understanding the effects of noise on fishes and invertebrates[J], Reviews in Fish Biology & Fisheries 25(1) (2015), 39–64.

Joly

, Rocha

and Sousa

L.C.F.

, The strategic importance of teaching Operations Research for achieving high performance in the petroleum refining business[J], Education for Chemical Engineers 10 (2015), 1–19.

Islam

and Sun

A.Y.

, Quantification of CO2 masses trapped through free convection process in isothermal brine saturated reservoir[J], International Journal of Heat and Mass Transfer 87(8.) (2015), 128–137.

10.

Shen

and Ritter

, Forecasting volatility of wind power production[J], Applied Energy 176(8.15) (2016), 295–308.

11.

Pedersen

, Mai

and Hansen

, Online Slug Detection in Multi-phase Transportation Pipelines Using Electrical Tomography[J], IFAC-Papers On Line 48(6) (2015), 159–164.

12.

Yikai

, Trend of Digital Transformation Promotion Among Petroleum Enterprises[J], China Oil & Gas 26(01) (2019), 23–30.

13.

Chen

, Zhang

and Chen

, Study on pressure interval of near-miscible flooding by production gas Re-injection in QHD offshore oilfield[J], Journal of Petroleum ence and Engineering 157 (2017), 340–348.

14.

White

, Now is the time to digitalize, embrace new technologies[J], Offshore 77(6) (2017), 64–74.

15.

Ahmed

, Are cyber security risks deterring digitalization[J], Offshore Engineer 41(5) (2016), 82–83.

16.

Hussin

M.H.

, Rahim

A.A.

and Ibrahim

M.N.M.

, BU prepares to sound on on world stage[J], Measurement 78(2016) (2015), 90–103.

17.

Rassenfoss

, SPE Technical Directors Working Outside the Lines[J], Journal of Petroleum Technology 67(01) (2015), 53–57.

18.

Kovski

, Final Rule for Control of Offshore Drilling Issued With Changes on Flexibility, Deadlines[J], Environment Reporter 47(16) (2016), 1177–1178.

19.

Legare

, Kneebone

and Deangelis

, The spatiotemporal dynamics of habitat use by blacktip (Carcharhinus limbatus) and lemon (Negaprion brevirostris) sharks in nurseries of St. John, United States Virgin Islands[J], Marine Biology 162(3) (2015), 699–716.

20.

Prokof’ev , Yu

and Pek

A.A.

, Problems in estimation of the formation depth of hydrothermal deposits by data on pressure of mineralizing fluids[J], Geology of Ore Deposits 57(1) (2015), 1–20.

21.

Schmoor

K.A.

, Achmus

and Foglia

, Reliability of design approaches for axially loaded offshore piles and its consequences with respect to the North Sea[J], Journal of Rock Mechanics & Geotechnical Engineering 10(06) (2018), 108–117.

22.

Shujie

, Xiangqian

and Hua

, Upgrading, Transforming, and Standardizing of Offshore Oil Drilling Equipment in China[J], China Oil & Gas 23(03) (2016), 31–37.

23.

Zou

and Lei

, The Cauchy problem for compressible Navier–Stokes equations with shear viscosity and large data[J], Ztschrift Für Angewandte Mathematik Und Physik 66(5) (2015), 2305–2341.

24.

Evangelista

and Filippo

S.D.M.

, Some Limits in the Use of the MASW Technique in Soils with Inclined Layers[J], Geotechnical & Geological Engineering 33(3) (2015), 701–711.

25.

Fang

, Yu

Q.H.

and Xu

, The Underwater Project Management in ‘Dong Fang’ Offshore Oil Engineering[J], Applied Mechanics and Materials 508 (2014), 125–128.

26.

Bouejla

, Chaze

and Guarnieri

, A Bayesian network to manage risks of maritime piracy against offshore oil fields[J], Safety ence 68 (2014), 222–230.

27.

Noroozi

, Abbassi

and Mackinnon

, Effects of Cold Environments on Human Reliability Assessment in Offshore Oil and Gas Facilities[J], Human Factors 56(5) (2014), 825–834.

28.

Kim

I.H.

, Dan

and Kim

, Simulation-Based Optimization of Multistage Separation Process in Offshore Oil and Gas Production Facilities[J], Industrial & Engineering Chemistry Research 53(21) (2014), 8810–8820.

29.

Rochette

, International regulation of offshore oil and gas activities: time to head over the parapet[J], Cancer Genetics & Cytogenetics 73(2) (2014), 103–108.

For intelligent debugging management of offshore oil engineering with big data

Abstract

Keywords

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