Data Clustering for Uncertainty Reduction – A Case Study of Solids Transport in Oil/Gas Pipelines

Purpose This paper aims to establish the downhole CO2 partial pressure profile calculating method and then to make an economical oil country tubular goods (OCTG) anti-corrosion design. CO2 partial pressure is the most important parameter to the oil and gas corrosion research for these wells which contain sweet gas of CO2. However, till now, there has not been a recognized method for calculating this important value. Especially in oil well, CO2 partial pressure calculation seems more complicated. Based on Dolton partial pressure law and oil gas separation process, CO2 partial pressure profile calculating method in oil well is proposed. A case study was presented according to the new method, and two kinds of corrosion environment were determined. An experimental research was conducted on N80, 3Cr-L80 and 13Cr-L80 material. Based on the test results, 3Cr-L80 was recommended for downhole tubing. Combined with the field application practice, 3Cr-L80 was proved as a safety and economy anti-corrosion tubing material in this oil field. A proper corrosion parameter (mainly refers to CO2 partial pressure and temperature) can ensure a safety and economy downhole tubing anti-corrosion design. Design/methodology/approach Based on Dolton partial pressure law and oil gas separation process, CO2 partial pressure profile calculating method in oil well is proposed. An experimental research was conducted on N80, 3Cr-L80 and 13Cr-L80 material. A field application practice was used. Findings It is necessary to calculate the CO2 partial pressure properly to ensure a safety and economy downhole tubing (or casing) anti-corrosion design. Originality/value The gas and oil separation theory and corrosion theory are combined together to give a useful method in downhole tubing anti-corrosion design method.

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Identification and Mitigation of a Landslide Threatening Four Operating Natural Gas Pipelines

Volume 3: Operations, Monitoring, and Maintenance; Materials and Joining ◽

10.1115/ipc2020-9743 ◽

2020 ◽

Author(s):

Amir Ahmadipur ◽

Alexander McKenzie-Johnson ◽

Ali Ebrahimi ◽

Anthony H. Rice

Keyword(s):

Natural Gas ◽

Landslide Hazard ◽

Management Process ◽

Gas Pipelines ◽

Hazard Management ◽

Natural Gas Pipelines ◽

South Central ◽

Subsurface Investigation ◽

Landslide Stabilization

Abstract This paper presents a case study of a landslide with the potential to affect four operating high-pressure natural gas pipelines located in the south-central US state of Mississippi. This case study follows a landslide hazard management process: beginning with landslide identification, through pipeline monitoring using strain gauges with an automated early alert system, to detection of landslide movement and its effects on the pipeline, completion of a geotechnical subsurface investigation, conceptual geotechnical mitigation planning, landslide stabilization design and construction, and stress relief excavation. Each step of the landslide hazard management process is described in this case study.

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The Use of AHP for IT Project Priorization – A Case Study for Oil & Gas Company

Procedia Computer Science ◽

10.1016/j.procs.2015.07.076 ◽

2015 ◽

Vol 55 ◽

pp. 1097-1105 ◽

Cited By ~ 7

Author(s):

Adriano José da Silva Neves ◽

Roberto Camanho

Keyword(s):

It Project ◽

Oil Gas

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Semiparametric Estimation and Panel Data Clustering Analysis Based on D-Vine and C-Vine

Mathematical Problems in Engineering ◽

10.1155/2018/5840296 ◽

2018 ◽

Vol 2018 ◽

pp. 1-10

Author(s):

Hong Li ◽

Yuantao Xie ◽

Juan Yang ◽

Di Wang

Keyword(s):

Panel Data ◽

Clustering Analysis ◽

Data Clustering ◽

Semiparametric Estimation ◽

Similarity Measurement ◽

Model Estimation ◽

Similarity Coefficients ◽

Clustering Model ◽

Compound Model

This paper proposed a panel data clustering model based on D-vine and C-vine and supported a semiparametric estimation for parameters. These models include a two-step inference function for margins, two-step semiparameter estimation, and stepwise semiparametric estimation. In similarity measurement, similarity coefficients are constructed by a multivariate Hierarchical Nested Archimedean Copula (HNAC) model and compound PCC models, which are HNAC and D-vine compound model and HNAC and C-vine compound model. Estimation solutions and models evaluation are given for these models. In the case study, the clustering results of HNAC and D-vine compound model and HNAC and C-vine compound model are given, and the effect of different copula families on clustering results is also discussed. The result shows the models are effective and useful.

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