Instantaneous Probability of Uncontrolled External Leakage During the Production Phase of a Subsea Well

2013 ◽  
Author(s):  
Andre L. R. Alves ◽  
Theodoro A. Netto
Keyword(s):  
Failure Rate ◽  
Failure Modes ◽  
Probability Distributions ◽  
Base Case ◽  
Component Reliability ◽  
Production Phase ◽  
Common Cause Failures ◽  
Closed Position ◽  
The Impact

This work develops a methodology for evaluating the uncontrolled external leakage probability of a subsea well during the production phase. Based on a barrier diagram, an algorithm for possible leak paths identification is proposed, considering different operation modes: gas lift operation, free flowing or well closed at the subsea Xmas Tree. Considering the equivalency between these paths and the minimum cut sets from a fault tree modeling, the uncontrolled external leakage probability is calculated using the upper bound approximation. The effect of common cause failures is considered for the failure mode fail-to-close-valve. The instantaneous availability function of each component is modeled to represent the maintenance strategy applied. Non repairable, repairable and periodically tested items are used. For the latter, a nomenclature to distinguish two subtypes is introduced: the PT-R and PT-NR models, respectively Periodically Tested Repairable, and Periodically Tested Non Repairable. Probability distributions parameters are roughly estimated in order to make a case study. The failure rate functions determined are used as input for the proposed model, regarding the following failure modes: fail-to-close, external-leakage, and internal-leakage at the closed position. The objective of this section is to adjust a Weibull distribution, eliminate the usual assumption of constant failure rate and account for eventual wear-out effects. Finally, instantaneous probability results and sensitivity analysis are demonstrated for a base case study. Parameters like time between tests, inspections, and component reliability are varied in order to identify the impact on the uncontrolled external leakage probability. Therefore, the main objective is to propose a model that could support decision making on the well integrity management system during the production phase of a subsea well. To make this possible, reliable input data should be further considered.

Probability of Uncontrolled External Leakage During the Production Phase of a Subsea Well

2020 ◽  
Vol 143 (1) ◽  
Author(s):  
André L. R. Alves ◽  
T. A. Netto
Keyword(s):  
Failure Modes ◽  
Base Case ◽  
Component Reliability ◽  
Production Phase ◽  
Distribution Parameters ◽  
Common Cause Failures ◽  
Integrity Management ◽  
Closed Position ◽  
The Impact

Abstract This work presents a methodology for evaluating the uncontrolled external leakage probability of a subsea well during the production phase. Based on a barrier diagram, an algorithm for possible leak path identification is proposed, considering different operation modes: gas lift operation, free-flowing, or well closed at the subsea Christmas tree. Considering the equivalency between these paths and the minimum cut sets from a fault tree modeling, the uncontrolled external leakage probability is calculated using the upper bound approximation. The effect of common cause failures is considered for the failure mode fail-to-close-valve. The instantaneous availability function of each component is considered. Non-repairable, repairable, and periodically tested items are used. Probability distribution parameters are estimated in order to make a case study. The failure rate functions determined are used as input for the proposed model, regarding the following failure modes: fail-to-close, external-leakage, and internal-leakage at the closed position. Finally, failure probability results and sensitivity analysis are demonstrated for a base case study. Parameters like time between tests, inspections, and component reliability are varied in order to identify the impact on the uncontrolled external leakage probability. The main objective of the proposed methodology is to support decision-making on the well integrity management system during the production phase of a subsea well. To this end, actual and reliable input data should be considered.

An Assessment of Uncertainty in Design Factors and Strain-Rate Inputs for Environmentally-Assisted Fatigue and Related Margins

2020 ◽  
Author(s):  
Y. S. Garud
Keyword(s):  
Strain Rate ◽  
Probability Of Failure ◽  
Pressure Vessels ◽  
Base Case ◽  
Component Reliability ◽  
Typical Application ◽  
Class 1 ◽  
Explicit Consideration ◽  
The Impact ◽  
Design Factors

Abstract In the case of ASME Class 1 pressure vessels and piping code, as in other similar codes, the design adequacy for fatigue is based on the cumulative usage factor (CUF), with recent augmentation to account for possible environmental effects. This deterministic quantification utilizes several engineering parameters (inputs) and (multiplicative) empirical factors. Although the fixed values of some of these design factors and S–N curves are based on underlying experimental data, the associated uncertainties are not explicit in the resulting fatigue assessment that is effectively based on the singular, calculated quantities of CUF and Fen, projected for a specified service. As such, the resulting fatigue margin and associated conservatism remain implicit or inconsistent and unquantifiable. At the same time, there is an increased demand for either extending the life of existing systems or for new systems with economically viable or better optimized fatigue designs. One approach to address this is to use a more realistic evaluation offered by probabilistic techniques that take into account the various uncertainties. Such an approach to supplement the deterministic analysis was recently proposed by the author keeping the existing and familiar framework of CUF based assessment, while satisfying acceptable component reliability to meet the fatigue design adequacy. The CUF formulation includes an explicit consideration of the k-factors (for material, loading history, surface and size effects) as adjustments to the S–N data. The objective of this paper is to assess the impact of k-factors and their uncertainty on the failure probability and on the number of load-cycles for specified target reliability. Also, similar assessment is made for the impact of strain-rate variable and its uncertainty on the allowable load-cycles. This is illustrated with a typical application of the CUF analysis of a safety injection nozzle safe-end. The approach taken consists of parametric analysis of the CUF-based probability of failure by individually removing the factors and/or their uncertainty, and comparing the results with the base case where all factors and associated uncertainties are maintained at their original values. Results of this analysis and their implications are discussed, along with a generally applicable relation between the deterministic CUF and the probability of failure.

scholarly journals Availability and LCOE Analysis Considering Failure Rate and Downtime for Onshore Wind Turbines in Japan

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3528
Author(s):  
Yuka Kikuchi ◽  
Takeshi Ishihara
Keyword(s):  
Failure Mode ◽  
Failure Rate ◽  
Wind Turbines ◽  
Failure Modes ◽  
Probability Distributions ◽  
Occurrence Rate ◽  
Baseline Scenario ◽  
Repair Cost ◽  
Effect Analysis ◽  
Onshore Wind

In this study, the availability and the levelized cost of energy (LCOE) are investigated considering failure rate and downtime for onshore wind turbines in Japan. The failure mode effect analysis is conducted using the wind turbine failure database collected by the New Energy and Industrial Technology Department Organization (NEDO). The normalized failure rate and downtime between Europe and Japan are comparable. The occurrence rate is similar between Europe and Japan, but the downtime in Japan is much longer than that of Europe. Three cost-reduction scenarios are then proposed to improve availability and to reduce LCOE using assumed failure rate and downtime in each mode based on the industry interview and best practices in Japan. The availability is improved from 87.4% for the baseline scenario to 92.7%, 95.5% and 96.4% for the three scenarios, and LCOE is also reduced from 13.7 Yen/kWh to 11.9, 11.0 and 10.7 Yen/kWh. Finally, the probability distributions of downtime and repair cost are obtained for each failure mode. It is found that the probability distributions of the failure modes with the shortest downtime show similar probability distributions regardless of the size of the assembly. The effects of downtime and repair-cost uncertainties on LCOE are also evaluated.

Optimizing Tubing and Liner Completion Design to Improve Gas Production from Existing Wells: Case Study for ADNOC Onshore Field Abu Dhabi, UAE

2021 ◽  
Author(s):  
Magdy Farouk Fathalla ◽  
Mariam Ahmed Al Hosani ◽  
Ihab Nabil Mohamed ◽  
Ahmed Mohamed Al Bairaq ◽  
Djamal Kherroubi ◽  
...  
Keyword(s):  
Gas Production ◽  
Base Case ◽  
Gas Wells ◽  
Production Rates ◽  
Liquid Loading ◽  
Gas Field ◽  
Well Production ◽  
Well Completion ◽  
The Impact

Abstract An onshore gas field contains several gas wells which have low–intermittent production rates. The poor production has been attributed to liquid loading issue in the wellbore. This study will investigate the impact of optimizing the tubing and liner completion design to improve the gas production rates from the wells. Numerous sensitivity runs are carried out with varying tubing and liner dimensions, to identity optimal downhole completions design. The study begins by identifying weak wells having severe gas production problems. Once the weak wells have been identified, wellbore schematics for those wells are studied. Simulation runs are performed with the current downhole completion design and this will be used as the base case. Several completion designs are considered to minimize the effect of liquid loading in the wells; these include reducing the tubing diameter but keeping the existing liner diameter the same, keeping the original tubing diameter the same but only reducing the liner diameter, extending the tubing to the Total Depth (TD) while keeping the original tubing diameter, and extending a reduced diameter tubing string to the TD. The primary cause of the liquid loading seems to be the reduced velocity of the incoming gas from the reservoir as it flows through the wellbore. A simulation study was performed using the various completion designs to optimize the well completion and achieve higher gas velocities in the weak wells. The results of the study showed significant improvement in gas production rates when the tubing diameter and liner diameter were reduced, providing further evidence that increased velocity of the incoming fluids due to restricted flow led to less liquid loading. The paper demonstrates the impact of downhole completion design on the productivity of the gas wells. The study shows that revisiting the existing completion designs and optimizing them using commercial simulators can lead to significant improvement in well production rates. It is also noted that restricting the flow near the sand face increases the velocity of the incoming fluid and reduces liquid loading in the wells.

Three Methods for Anticipating and Understanding Uncertainty of Outputs from Transportation and Land Use Models

2018 ◽  
Vol 2672 (49) ◽  
pp. 12-22 ◽  
Author(s):  
Guangmin Wang ◽  
Kara M. Kockelman
Keyword(s):  
Land Use ◽  
Convergence Rates ◽  
Probability Distributions ◽  
Uncertainty Propagation ◽  
Computing Time ◽  
Point Estimates ◽  
Land Use Models ◽  
Input Uncertainties ◽  
The Impact

This study demonstrates three methods for uncertainty propagation in transportation and land-use models (LUMs): Local Sensitivity Analysis with Interaction (LSAI), Monte Carlo (MC), and Bayesian Melding (BM). Two case-study settings are used to illustrate how these methods work, allowing for inter-method comparisons. LSAI can provide the sign of change implied by changes in model inputs, the relative importance of changes in different inputs, and a decomposition of changes in outputs due to the impact of inputs’ individual and interactive. LSAI is limited to relatively small-size problems because its computing time rises exponentially with the number of (groups of) inputs. Moreover, LSAI obtains only point estimates, while MC and BM methods can deliver entire distributions of each output through an understanding of the uncertainty in all model inputs and parameters. MC delivers each output’s distribution and requires hundreds of samples, especially for more accurate results. Fortunately, MC methods are especially useful for high-dimensional problems because convergence rates are not a function of model dimensionality and errors depend only on sample size and input uncertainties. BM delivers posterior distributions for model outputs, using prior probability distributions and likelihoods of inputs and parameters, along with validation of/comparison to intermediate model outputs. A BM approach can be extremely expensive, in terms of computing time, since it requires several hundred model runs.

On Measurement of Effective Silicon Backend Strength Using Bump Pull/Shear Techniques

2005 ◽  
Author(s):  
Sandeep Sane ◽  
Shalabh Tandon ◽  
Biju Chandran ◽  
Tsgereda Alazar ◽  
Leonard R. Sorenson
Keyword(s):  
Failure Modes ◽  
Tensile Force ◽  
Lead Free ◽  
Stress Exposure ◽  
Process Variables ◽  
First Case ◽  
Repeatability And Reproducibility ◽  
The Impact ◽  
Low K

Integrating a low-K ILD layer within silicon is key to reducing RC delays. However, low-K ILD materials typically have low mechanical strength, making their incorporation with lead free interconnects an industry-wide challenge. It is well known that conversion to lead free first level interconnects increases die backend stresses due to the higher melting temperature and increased solder stiffness. The paper will focus on the measurement of the effective silicon backend strength after subjecting the dice to different fabrication and assembly steps. The effective strength will also be evaluated post reliability stress exposure to eventually understand the life of these films. The paper will describe how a commercially available Dage 4000 tool was modified for this application. Bump pull was carried out using a 100μm tweezers, while bump shear used 1mil (25.4μm) wide stylus. Static and dynamic calibration was first carried out to ensure repeatability and reproducibility of the results. Peak force and failure modes were used as metrics to compare the effectiveness of different experimental legs. Traditional failure analysis approach of mechanical polishing, or when needed, use of FIB for sample preparation, with subsequent SEM/EDX analysis was utilized to understand the failure mechanism. Data suggests that shear and pull lead to different failure modes. Bump shear mainly led to failure at the bump/polyimide interface and did not necessarily correspond to the weakest layer or interface in the silicon backend. Whereas bump-pull, which applies tensile force to the stack up, lead to failures in the weakest layer, typically the low-K ILD, in the silicon backend. Hence, bump pull provided the advantage over shear as it allowed evaluation of the weakest interface in the stack up. Two case studies are discussed to demonstrate on how bump pull/shear metrologies were used to understand the impact of different assembly/FAB process variables and highly accelerated steam test (HAST) reliability stress on silicon backend strength. First case study shows influence of assembly flux on silicon backend strength, while second case study describes impact of HAST on different FAB backend processes.

scholarly journals Reliability of Supply and the Impact of Weather Exposure and Protection System Failures

2020 ◽  
Vol 11 (1) ◽  
pp. 182
Author(s):  
Erlend Sandø Kiel ◽  
Gerd Hovin Kjølle
Keyword(s):  
System Reliability ◽  
Failure Modes ◽  
Extreme Weather ◽  
Test System ◽  
Protection System ◽  
Electrical Transmission ◽  
System Failures ◽  
Reliability Indices ◽  
The Impact

Extreme weather is known to cause failure bunching in electrical transmission systems. However, protection systems can also contribute to the worsening of the system state through various failure modes—spontaneous, missing or unwanted operation. The latter two types of failures only occur when an initial failure has happened, and thus are more likely to happen when the probability of failure of transmission lines is high, such as in an extreme weather scenario. This causes an exacerbation of failure bunching effects, increasing the risk of blackouts, or High Impact Low Probability (HILP) events. This paper describes a method to model transmission line failure rates, considering both protection system reliability and extreme weather exposure. A case study is presented using the IEEE 24 bus Reliability Test System (RTS) test system. The case study, using both an approximate method as well as a time-series approach to calculate reliability indices, demonstrates both a compact generalization of including protection system failures in reliability analysis, as well as the interaction between weather exposure and protection system failures and its impact on power system reliability indices. The results show that the inclusion of protection system failures can have a large impact on the estimated occurrence of higher order contingencies for adjacent lines, especially for lines with correlated weather exposure.

Reliability block diagram (RBD) and fault tree analysis (FTA) approaches for estimation of system reliability and availability – a case study

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Balaraju Jakkula ◽  
Govinda Raj Mandela ◽  
Murthy Ch S N
Keyword(s):  
Failure Modes ◽  
Block Diagram ◽  
Probability Distributions ◽  
Fault Tree Analysis ◽  
Likelihood Estimation ◽  
Parametric Estimation ◽  
Data Sets ◽  
Content Type ◽  
Best Fit

PurposeIn the present worldwide situation, the survival of a business is a major crucial aspect. The business cannot be succeeded unless it produces the anticipated production levels. Achievement of this can be possible only by maintaining the equipment into an adequate level. Load-Haul-Dumpers (LHDs), as the main workhorse and massive transporting machines, are highly utilized in underground mining operations. Despite the usage of LHDs, these are prone to the uneven and unexpected occurrence of potential failures. These are causes to minimize the production and productivity of capital intensive equipment. To get a good profitability index, it is very necessary to have the required levels of equipment reliability and availability. Estimation of reliabilities and availabilities play a critical role in the performance evaluation of equipment.Design/methodology/approachBy keeping the significance of the present research work in view in this research paper one of the well appropriate techniques such as fault tree analysis (FTA) was utilized to assess the reliability of the LHD system based on the function flow diagram. Best fit distribution of data sets were made by the utilization of Kolmogorov–Smirnov (K-S) test. Parametric estimation of theoretical probability distributions was done by utilizing the maximum likelihood estimation (MLE). Failure rate of each LHD system has computed based on the best fit results from “Isograph Reliability Workbench 13.0”. Reliability configuration of each LHD system has modeled using reliability block diagram (RBD), as well as the FTA.FindingsIndependent and identical distribution (IID) assumption of data sets was validated through statistic U-test (Chi Squared test). On the basis of test results, the data sets are in accordance with IID assumption. Therefore renewal process approach has been utilized for further investigation. Allocations of best fit distribution of data sets were made by the utilization ofK-S test. Parametric estimation of theoretical probability distributions was made by utilizing maximum likelihood estimation (MLE) method. Reliability of each individual subsystem has been computed according to the best fit distribution. The deductive method called RBD was utilized to investigate the given system reliability by analyzing with graphical representations of logic system and observed highest percentage of reliability as 69.44% (LH29). FTA has been utilized to investigate the availability percentage of a system and observed highest percentage value as 79.51% (LH29). This technique also helps to identify the most critical parts/cut sets by using Fussell-Vesely (F-V) importance measure.Research limitations/implicationsAs the reliability analysis is one of the complex techniques, it requires strategic decision-making knowledge for the selection of methodology to be used. As the present case study was from a public sector company, operating under financial constraints the conclusions/findings may not be universally applicable.Originality/valueThe present study throws light on this equipment that need a tailored maintenance schedules, partly due to the peculiar mining conditions, under which they operate. This analysis provides the information on several aspects such as present working condition of the machines, occurrence of various potential failure modes, influence of failure modes on its performance and reliable life aspects etc. Also, these investigations asses the forecasting of necessary managerial practices or control measures like possible design modifications and replacement actions of components to ensure the required levels of availability and utilization of the equipment. Both qualitative and quantitative analysis of FTA has been performed to determine the minimal/most influencing cut sets of the system and to estimate overall system availability within the work environment. Based on the computed results reasons for performance drop of each machine was identified and suitable recommendations were suggested to improve the performance of capital intensive systems.

Using productivity concept to predict material demand

2021 ◽  
Vol 14 ◽  
Author(s):  
Hui-Hsin Huang
Keyword(s):  
Characteristic Function ◽  
Probability Function ◽  
Probability Distributions ◽  
Demand Forecasting ◽  
Model Development ◽  
General Function ◽  
Input Material ◽  
Proposed Model ◽  
The Impact

Background: The issue of material demands prediction has been researched in industrial study and materials/ manufacturing technology many years ago. The previous researches based on stochastic model to discuss the quantities prediction of material demand. Some of them focus on multi-suppliers with characteristic function. Some use the information of past ordering quantities and ordering recency time. In these previous models, there is less study to discuss the impact of cost on material demand forecasting. Thus, this paper considers the productivities concept to make cost balance when forecasting material demand. The different probability distributions are demonstrated to portray the input (material demand) and output(cost). Methods: A case study with its empirical data is released to derive the probability function of cost and estimate the parameters of the proposed model. Results: The proposed model can extend to different distributions depending on different kind of cost or different type of industries and is more widely application. Conclusion: To consider manufacture's productivity, this model can help manager to control their cost and make a balance when ordering their materials. The model development of cost release a general function which makes it possible to extend different distributions depending on different kind of cost or different type of industries.

The Economics of Biomass Logistics and Conversion Facility Mobility: An Oregon Case Study

2018 ◽  
Vol 34 (1) ◽  
pp. 57-72 ◽  
Author(s):  
Michael David Berry ◽  
John Sessions
Keyword(s):  
Supply Chain ◽  
Large Scale ◽  
Biomass Conversion ◽  
The United States ◽  
Mixed Integer ◽  
Modular System ◽  
Base Case ◽  
Biomass Availability ◽  
The Impact

Abstract. This article presents an analysis of transportable biomass conversion facilities to evaluate the conceptual and economic viability of a highly mobile and modular biomass conversion supply chain in the Pacific Northwest of the United States. The goal of this work is to support a broader effort to more effectively and sustainably use residual biomass from commercial harvesting operations that are currently piled and burned as part of site preparation. A structural representation is first developed to include sources of biomass feedstock, distributed preprocessing hubs (centralized landings), and centralized processing facilities (biomass to product conversion sites) to produce desired products and byproducts. A facility costing model was developed to evaluate potential economics of scale, which then informed the optimization study. A mixed integer linear programming model was developed to characterize, evaluate, and optimize biomass collection, extraction, logistics, and facility placement over a regional landscape from a strategic level to evaluate the mobility concept. The objective was to minimize supply chain operational costs in order to quantify financial advantages and identify challenges of the proposed system modularity and mobility. A Lakeview, Oregon case study was evaluated with an assumed modular biochar facility servicing the region. In particular, we review economies of scale, mobility, energy costs, and biomass availability tradeoffs. This analysis points towards a modular system design of movement frequency between 1 to 2 years being most viable in the conditions evaluated. It was found that the impact of plant movement, scale, and biomass availability can increase supply chain costs by $11/BDMT ($10/BDT), $33/BDMT ($30/BDT), and $22/BDMT ($20/BDT) above the base case cost of $182/BDMT ($165/BDT) for a large-scale facility [45,000 BDMT yr-1(50,000 BDT yr-1)]in the conditions evaluated. Additionally, potential energy cost savings of a non-mobile modular stationary site as compared to one which utilizes off-grid electrical powers about $11/BDMT ($10/BDT) for a biochar facility. From the cases evaluated, a large-scale plant with limited mobility would be preferred under low availability of biomass conditions, whereas a stationary grid-connected plant would be more cost effective under higher availability conditions. Results depend greatly on the region, assumed harvest schedule, biomass composition, and governing biomass plant assumptions. Keywords: Biomass products, Biomass supply, Facility location, Mixed integer programming, Strategic planning, Transportable plants.

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