Application of fine managed pressure drilling technique in complex wells with both blowout and lost circulation risks

Yan, Ling; Wu, Huisheng; Yan, Yan

doi:10.1016/j.ngib.2015.07.010

Cited by 17 publications

(3 citation statements)

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“…Therefore, the Mg‐Gd‐Ni alloy containing Ni‐containing LPSO phase might have a superior strength but high corrosion rate. Such properties characteristics were suitable for the application in the field of temporary plugging tools in oil/gas wells . Obviously, the mechanical and corrosion properties of the Mg‐Gd‐Ni alloys should be closely related to the volume fraction of LPSO phase.…”

Section: Introductionmentioning

confidence: 99%

Effects of volume fraction of Ni‐containing LPSO phase on mechanical and corrosion properties of Mg‐Gd‐Ni alloys

Han

Zhang

Yang³

et al. 2018

Materials & Corrosion

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Mg‐Gd‐Ni alloys with same Gd/Ni mole ratios but different volume fraction of Ni‐containing LPSO phase were prepared. The effects of the volume fraction of Ni‐containing LPSO phase on the mechanical and corrosion properties of Mg‐Gd‐Ni alloys were systematically investigated. It was found that the strength was remarkably enhanced but the plasticity was decreased with the increase of the volume fraction of Ni‐containing LPSO phase. The electro‐potential distribution characteristic shows that the Ni‐containing LPSO phase had a lower electro‐potential than the Mg matrix, which was related to the existence of Ni in LPSO phase. Consequently, Ni‐containing LPSO phase was preferentially eroded during micro‐galvanic corrosion. High volume fraction LPSO phases accelerated the corrosion rate of Mg‐Gd‐Ni alloy. The detailed corrosion mechanisms were discussed in the present study.

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Section: Introductionmentioning

confidence: 99%

Effects of volume fraction of Ni‐containing LPSO phase on mechanical and corrosion properties of Mg‐Gd‐Ni alloys

Han

Zhang

Yang³

et al. 2018

Materials & Corrosion

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“…A loss of circulation occurs when the bottom hole pressure in the wellbore is higher than the formation pressure, allowing (or forcing) the drilling fluid to flow into the formation. Several researchers have focused on the effects of lost circulation (Shen, 2015;Yan et al, 2015), and proposed measures to reduce such effects (Alexander, 1989;Sheremetov et al, 2008). Lost circulation is usually accompanied by wellbore stability problems, damage of reservoir near well bottom, and stuck pipe, and these are the main reasons why kick and even blowout can occur as a consequence.…”

Section: Introductionmentioning

confidence: 99%

A DBN-Based Risk Assessment Model for Prediction and Diagnosis of Offshore Drilling Incidents

2018

Bayesian Networks in Fault Diagnosis

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Drilling operations of offshore oil and gas fields are characterized by high reliance on advanced technology, high risk, and high costs due to operating in harsh ocean environments, under complicated geological factors, and extreme operating condition. Lost circulation or well "kick" are examples of hazardous events that may occur while drilling wells and such events may develop into a blowout accident if not handled. Identification and analysis of root causes and consequences are effective measures to prevent serious accidents from happening. The risk of having a blowout may change with time, depending on the stage of the drilling operation, and such kind of dynamics should be captured in risk assessment. This paper presents an approach for determining the conditional probabilities of hazardous events and their consequences. The approach includes models that take into account the influence of degradation and (if used in operation) new real-time information which represents the change in a state of a model parameter (such as state change of mud density) that can be captured while the drilling operation is ongoing. The approach presents a newly-developed model based on the basic theory of Dynamic Bayesian network (DBN) and this proposed model can incorporate some additional nodes to handle the uncertainty issues involving the model uncertainty and relevant parameters' uncertainty and also consider the effect of degradation, which are missed in other papers when using the DBN method for risk assessment of similar systems and operations. The main objective of this newly-developed model is to demonstrate how dynamic risk assessments can be used for incident prediction evolution as well as root cause reasoning during offshore drilling operation, given that a specific event has occurred. A bowtie model is established firstly to link the potential incident scenarios with pressure regimes and formation load capacity, and then the model is translated into a DBN. DBN inference is adapted to perform predictive and diagnostic analysis in different time slices for risk assessment and root cause reasoning. A sensitivity analysis is carried out to find the relative importance of each root cause in generating the potential drilling incidents. A case study with focusing on lost circulation during three drilling scenarios is used to illustrate and verify the feasibility of the proposed approach.

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Section: Introductionmentioning

confidence: 99%

A DBN-based risk assessment model for prediction and diagnosis of offshore drilling incidents

Zhang

Zheng

et al. 2016

Journal of Natural Gas Science and Engineering

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Abstract:Drilling operations of offshore oil and gas fields are characterized by high reliance on advanced technology, high risk, and high costs due to operating in harsh ocean environments, under complicated geological factors, and extreme operating condition. Lost circulation or well "kick" are examples of hazardous events that may occur while drilling wells and such events may develop into a blowout accident if not handled. Identification and analysis of root causes and consequences are effective measures to prevent serious accidents from happening. The risk of having a blowout may change with time, depending on the stage of the drilling operation, and such kind of dynamics should be captured in risk assessment. This paper presents an approach for determining the conditional probabilities of hazardous events and their consequences. The approach includes models that take into account the influence of degradation and (if used in operation) new real-time information which represents the change in a state of a model parameter (such as state change of mud density) that can be captured while the drilling operation is ongoing.The approach presents a newly-developed model based on the basic theory of Dynamic Bayesian network (DBN) and this proposed model can incorporate some additional nodes to handle the uncertainty issues involving the model uncertainty and relevant parameters' uncertainty and also consider the effect of degradation, which are missed in other papers when using the DBN method for risk assessment of similar systems and operations. The main objective of this newly-developed model is to demonstrate how dynamic risk assessments can be used for incident prediction evolution as well as root cause reasoning during offshore drilling operation, given that a specific event has occurred. A bowtie model is established firstly to link the potential incident scenarios with pressure regimes and formation load capacity, and then the model is translated into a DBN. DBN inference is adapted to perform predictive and diagnostic analysis in different time slices for risk assessment and root cause reasoning. A sensitivity analysis is carried out to find the relative importance of each root cause in generating the potential drilling incidents. A case study with focusing on lost circulation during three drilling scenarios is used to illustrate and verify the feasibility of the proposed approach.Key words: Dynamic Bayesian network (DBN); drilling incidents; dynamic risk assessment; prediction of incident evolution; root cause reasoning Highlights: Potential incident scenarios with pressure regimes and weak formation are presented.  A newly-developed model based on Dynamic Bayesian Network is proposed for offshore drilling incidents.  Effects of model and parameter uncertainty are taken into account.  Prediction of risk evolution and root cause reasoning are performed based on the influence of degradation and occurred events.

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Application of fine managed pressure drilling technique in complex wells with both blowout and lost circulation risks

Cited by 17 publications

References 0 publications

Effects of volume fraction of Ni‐containing LPSO phase on mechanical and corrosion properties of Mg‐Gd‐Ni alloys

Effects of volume fraction of Ni‐containing LPSO phase on mechanical and corrosion properties of Mg‐Gd‐Ni alloys

A DBN-Based Risk Assessment Model for Prediction and Diagnosis of Offshore Drilling Incidents

A DBN-based risk assessment model for prediction and diagnosis of offshore drilling incidents

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