Wait on Weather WOW Impact Trending in Malaysia Water: Comprehensive Data Analytics Led to Safe and Optimum Well Planning and Offshore Execution

2021 ◽  
Author(s):  
Rahimah A Halim ◽  
M. Hatta Mhd Yusof ◽  
M. Hanafi M Khalid ◽  
Hao Xiang Wong ◽  
M. Zarkashi Sulaiman
Keyword(s):  
Risk Factor ◽  
Monsoon Season ◽  
Weather Condition ◽  
Oil And Gas Industry ◽  
Peninsular Malaysia ◽  
Distribution Analysis ◽  
Planning Stage ◽  
Drilling Operation ◽  
Drilling Rig ◽  
Operation Stage

Abstract Drilling operation in Malaysia are typically from offshore, thus offshore weather condition does contributed to the success or delay of a drilling operation. Wait on Weather (WOW) especially during monsoon season in Malaysia has impacted Operator's drilling operation, thus incurring additional cost to Operator. Monsoon season in Malaysia is typically from November to February every year. This paper will discuss and share the statistics of actual WOW happening from 2008 to 2019 in Malaysia water especially for jack-up rig (JUR) and tender assisted drilling rig (TADR) which are two common rigs in Malaysia water. The data was collected from one of the drilling operator in Malaysia. These data will be of assistance to Operator in better planning and executing drilling operation with the actual statistics as the risk factor. WOW is considered as non-productive time (NPT), thus NPT data gathering from Operators in Malaysia water were conducted. Data was then filtered to achieve the WOW data. WOW data was segregated between region in Malaysia which are Peninsular Malaysia (PM), Sabah (SB) and Sarawak (SK) as well as rig type, which are JUR and TADR. Distribution analysis were made to calculate the average and observe the maximum numbers of actual WOW occurrence. Further analysis was made to zoom into monsoon season in Malaysia which typically in November to February. 11 years data is generally good coverage for the analysis since it covers the up and down of oil and gas industry. Analysis was also done for both mob/demob and operation stage where it can be observed that WOW for mob/demob stage during monsoon season is significantly higher compared to operation stage. At the end of the analysis, the average or maximum numbers of WOW will be shared, and it will be used as recommendation for future projects to consider these figures as WOW risk factor and embed in the planning stage. This paper will help not only Operators in Malaysia water but the host authority on understanding the WOW risk factor during monsoon season. As WOW is not something that can be predicted, utilizing the standard results from actual statistic data for the past 11 years will assist engineers to incorporate the WOW risk factor during planning and execution stage. Rig and project sequencing can be optimized with understanding of WOW impact thus reducing the value leakage during operation due to WOW.

Understanding the Impact of Monsoon Season in Malaysia Water Based on Data Analytics for Planning and Executing Drilling Operation

2021 ◽  
Author(s):  
Rahimah A. Halim ◽  
M. Hatta M. Yusof ◽  
M. Hanafi M. Khalid ◽  
Hao Xiang Wong ◽  
M. Aizat Abu Bakar ◽  
...  
Keyword(s):  
Risk Factor ◽  
Monsoon Season ◽  
Weather Condition ◽  
Oil And Gas Industry ◽  
Distribution Analysis ◽  
Planning Stage ◽  
Drilling Operation ◽  
Drilling Rig ◽  
Operation Stage ◽  
The Impact

Abstract Drilling operation in Malaysia are typically from offshore, thus offshore weather condition does contributed to the success or delay of a drilling operation. Wait on Weather (WOW) especially during monsoon season in Malaysia has impacted Operator's drilling operation, thus incurring additional cost to Operator. Monsoon season in Malaysia is typically from November to February every year. This paper will discuss and share the statistics of actual WOW happening from 2008 to 2019 in Malaysia water especially for jack-up rig (JUR) and tender assisted drilling rig (TADR) which are two common rigs in Malaysia water. The data was collected from one of the drilling operator in Malaysia. These data will be of assistance to Operator in better planning and executing drilling operation with the actual statistics as the risk factor. WOW is considered as non-productive time (NPT), thus NPT data gathering from Operators in Malaysia water were conducted. Data was then filtered to achieve the WOW data. WOW data was segregated between region in Malaysia which are Peninsular Malaysia (PM), Sabah (SB) and Sarawak (SK) as well as rig type, which are JUR and TADR. Distribution analysis were made to calculate the average and observe the maximum numbers of actual WOW occurrence. Further analysis was made to zoom into monsoon season in Malaysia which typically in November to February. 11 years data is generally good coverage for the analysis since it covers the up and down of oil and gas industry. Analysis was also done for both mob/demob and operation stage where it can be observed that WOW for mob/demob stage during monsoon season is significantly higher compared to operation stage. At the end of the analysis, the average or maximum numbers of WOW will be shared, and it will be used as recommendation for future projects to consider these figures as WOW risk factor and embed in the planning stage. This paper will help not only Operators in Malaysia water but the host authority on understanding the WOW risk factor during monsoon season. As WOW is not something that can be predicted, utilizing the standard results from actual statistic data for the past 11 years will assist engineers to incorporate the WOW risk factor during planning and execution stage. Rig and project sequencing can be optimized with understanding of WOW impact thus reducing the value leakage during operation due to WOW.

scholarly journals Changing Epidemiology of Acute Respiratory Infections in Under-Two Children in Dhaka, Bangladesh

2022 ◽  
Vol 9 ◽  
Author(s):  
Karine Vidal ◽  
Shamima Sultana ◽  
Alberto Prieto Patron ◽  
Irene Salvi ◽  
Maya Shevlyakova ◽  
...  
Keyword(s):  
Risk Factors ◽  
Risk Factor ◽  
Low Income ◽  
Respiratory Infections ◽  
Monsoon Season ◽  
Low Income Countries ◽  
Health Study ◽  
Acute Respiratory Infections ◽  
Respiratory Pathogens ◽  
Prevention Measures

Objectives: Risk factors for acute respiratory infections (ARIs) in community settings are not fully understood, especially in low-income countries. We examined the incidence and risk factors associated with ARIs in under-two children from the Microbiota and Health study.Methods: Children from a peri-urban area of Dhaka (Bangladesh) were followed from birth to 2 years of age by both active surveillance of ARIs and regular scheduled visits. Nasopharyngeal samples were collected during scheduled visits for detection of bacterial facultative respiratory pathogens. Information on socioeconomic, environmental, and household conditions, and mother and child characteristics were collected. A hierarchical modeling approach was used to identify proximate determinants of ARIs.Results: Of 267 infants, 87.3% experienced at least one ARI episode during the first 2 years of life. The peak incidence of ARIs was 330 infections per 100 infant-years and occurred between 2 and 4 months of age. Season was the main risk factor (rainy monsoon season, incidence rate ratio [IRR] 2.43 [1.92–3.07]; cool dry winter, IRR 2.10 [1.65–2.67] compared with hot dry summer) in the first 2 years of life. In addition, during the first 6 months of life, young maternal age (<22 years; IRR 1.34 [1.01–1.77]) and low birth weight (<2,500 g; IRR 1.39 [1.03–1.89]) were associated with higher ARI incidence.Conclusions: Reminiscent of industrialized settings, cool rainy season rather than socioeconomic and hygiene conditions was a major risk factor for ARIs in peri-urban Bangladesh. Understanding the causal links between seasonally variable factors such as temperature, humidity, crowding, diet, and ARIs will inform prevention measures.

Altitude as a risk factor for the development of hypospadias. Geographical cluster distribution analysis in South America

2016 ◽  
Vol 12 (5) ◽  
pp. 307.e1-307.e5 ◽  
Author(s):  
Nicolas Fernández ◽  
Armando Lorenzo ◽  
Darius Bägli ◽  
Ignacio Zarante
Keyword(s):  
Risk Factor ◽  
South America ◽  
Distribution Analysis ◽  
Cluster Distribution ◽  
Geographical Cluster

Petroleum Well Blowouts as a Threat to Drilling Operation and Wellbore Sustainability: Causes, Prevention, Safety and Emergency Response

2021 ◽  
Author(s):  
Hamzeh Ghorbani ◽  
◽  
Mohammad Reza Abdali ◽  
Nima Mohamadian ◽  
David A. Wood ◽  
...  
Keyword(s):  
Emergency Response ◽  
Surface Damage ◽  
Lessons Learned ◽  
Fire Control ◽  
Safety Measures ◽  
Well Control ◽  
Drilling Operation ◽  
Drilling Rig ◽  
Petroleum Wells ◽  
Safety Systems

Sustainability in petroleum wells drilling operation systems strongly depends on the use of sustainable materials and a set of technical and safety measures that lead to the survival and proper operation of drilling rig equipment's and personnel. Adherence to the highest levels of standards of tools, materials and methods, although always recommended as the most important option for advancing a safe drilling operation and completing the well efficiently, low risk and stable, but drilling operation is inherently a battle with underground challenges and unexpected dangers. Learning from past such well blowout events and the problems they pose to rapidly control is essential to reduce future impacts including injuries, damage and emissions. Such analysis offers guidance for adapting working practices to improve both prevention and emergency response to such incidents. The causes of blowout during drilling and the necessary technical and safety measures to adopt are reviewed, highlighting how best practices can prevent blowout incidents by improving responses to early warning signals. The particular risks associated with potential shallow gas blowouts are identified and described with the aid of a case study associated with a catastrophic blowout of an onshore well in Iran and the methods used to ultimately control it. The multiple causes of the incident relating to defects in safety systems, equipment and operating procedures are addressed. Lessons learned from the incident reveal the complexity of well control once a blowout incident has occurred and developed into a surface fire. from the stage of the incident to fire control. There is a need for further research into top-hole well kill techniques for wells in a blowout state, as drilling bottom-hole relief wells takes substantial time, during which much surface damage, resource loss and emission typically occurs.

Quantifying Economic Uncertainties and Risks in the Oil and Gas Industry

2021 ◽  
pp. 154-184
Author(s):  
Sorin Alexandru Gheorghiu ◽  
Cătălin Popescu
Keyword(s):  
Business Performance ◽  
Oil And Gas ◽  
Water Injection ◽  
Oil And Gas Industry ◽  
Oil Field ◽  
Gas Industry ◽  
Field Development ◽  
Drilling Rig ◽  
Oil Field Development ◽  
Oil Gas

The present economic model is intended to provide an example of how to take into consideration risks and uncertainties in the case of a field that is developed with water injection. The risks and uncertainties are related, on one hand to field operations (drilling time, delays due to drilling problems, rig failures and materials supply, electric submersible pump [ESP] installations failures with the consequences of losing the well), and on the other hand, the second set of uncertainties are related to costs (operational expenditures-OPEX and capital expenditures-CAPEX, daily drilling rig costs), prices (oil, gas, separation, and water injection preparation), production profiles, and discount factor. All the calculations are probabilistic. The authors are intending to provide a comprehensive solution for assessing the business performance of an oil field development.

Blowout preventer (BOP) risk model to assist critical decisions in offshore drilling

2013 ◽  
Vol 53 (1) ◽  
pp. 209
Author(s):  
Inge Alme ◽  
Angel Casal ◽  
Trygve Leinum ◽  
Helge Flesland
Keyword(s):  
Nuclear Power ◽  
Power Plants ◽  
Oil And Gas ◽  
Risk Model ◽  
Oil And Gas Industry ◽  
Third Party ◽  
Risk Level ◽  
Main Task ◽  
Offshore Drilling ◽  
Drilling Rig

The BOP is a critical safety system of an offshore drilling rig, as shown in the 2010 Macondo accident. A challenge for the oil and gas industry is to decide what to do when the BOP is failing. Pulling the BOP to the surface during operations for inspection and testing is a costly and timely operation. Many of the potential failures are not critical to overall safety as multiple levels of redundancy are often available. Scandpower and Moduspec, both subsidiaries of Lloyd’s Register, have developed a BOP risk model that will assist the industry make the pull or no pull decisions. Scandpower’s proprietary software RiskSpectrum is used for the modelling. This software is used for equivalent decision support in the nuclear power industry, where the risk levels of total nuclear power plants are monitored live by operators in the control rooms. By modelling existing BOPs and their submerged control systems, and using risk monitor software for keeping track on the status of the BOP subsystems and components, the industry is able to define the real-time operational risk level the BOP is operating at. It, therefore, allows the inclusion for sensitivity modelling with possible faulty components factored in the model. The main task of the risk model is to guide and support energy companies and regulators in the decision process when considering whether to pull the BOP for repairs. Moreover, it will help the communication with the regulators, since the basis for the decisions are more traceable and easier to follow for a third party.

ASSESSMENT OF THE SPATIAL VARIATION AND SOURCE APPORTIONMENT OF AIR POLLUTION BASED ON CHEMOMETRIC TECHNIQUES: A CASE STUDY IN THE PENINSULAR MALAYSIA

2015 ◽  
Vol 77 (1) ◽  
Author(s):  
Hamza Ahmad Isiyaka ◽  
Hafizan Juahir ◽  
Mohd Ekhwan Toriman ◽  
Azman Azid ◽  
Barzani Mohd Gasim ◽  
...  
Keyword(s):  
Air Pollution ◽  
Spatial Variation ◽  
Source Apportionment ◽  
Anthropogenic Activities ◽  
Weather Condition ◽  
Principal Component ◽  
Peninsular Malaysia ◽  
Air Pollutant ◽  
Secondary Pollutants ◽  
Chemometric Techniques

This study aims to investigate the spatial variation in the source of air pollution, identify the percentage contribution of each pollutant and apportion the mass contribution of each source category using chemometric techniques. Hierarchical agglomerative cluster analysis (HACA) successfully grouped the five air monitoring sites into three groups (cluster 1, 2 and 3). Principal component analysis (PCA) was used to spot out the sources of air pollution which are attributed to anthropogenic activities. Multiple linear regression (MLR) was used to develop an equation model that explains the contribution of pollutants in each cluster. However, it was observed that particulate matter (PM10) and Ozone (O3) are the most significant pollutants influencing the value of air pollutant index (API). Meanwhile, the source apportionment indicates that cluster 1 is influenced by gas and non-gas pollutants to a degree of 84%, weather condition 15% and 1% by gas and secondary pollutants. Cluster 2 is affected by gas and secondary pollutants to a tune of 87% and 13% by weather condition while cluster 3 is apportioned with 98% secondary gas and non-gas pollutants and 2% weather condition. This study reveals the usefulness of chemometric technique in modeling and reducing the cost and time of monitoring redundant stations and parameters.

Theoretical review on critical risk factors in oil and gas construction projects in Yemen

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mukhtar A Kassem ◽  
Muhamad Azry Khoiry ◽  
Noraini Hamzah
Keyword(s):  
Risk Factors ◽  
Risk Factor ◽  
Literature Review ◽  
Construction Projects ◽  
Oil And Gas ◽  
Project Success ◽  
Oil And Gas Industry ◽  
Gas Industry ◽  
Content Type ◽  
Oil And Gas Sector

PurposeThe oil and gas construction projects are affected negatively by the drop in oil price in recent years. Thus, most engineering, procurement and construction (EPC) companies are opting to optimize the project mainly to mitigate the source of risks in construction to achieve the project expectation. Risk factors cause a threat to the project objectives regarding time, cost and quality. It is additionally a vital component in deviating from the client's expectation of productivity, safety and standards. This research aims to investigate the causes of risk in the oil and gas construction projects in Yemen.Design/methodology/approachA comprehensive literature review from various sources including books, conference proceedings, the Internet project management journals and oil and gas industry journals was conducted to achieve the objectives of this study. This initial work was predicated strictly on a literature review and the judgments of experts to develop the risk factor framework for the oil and gas construction projects in Yemen.FindingsThe authors found a few studies related to risk factors in oil and gas construction projects and shared a similar view about general construction projects. However, only a fraction of the factors accepted have included the variances of other studies on a regional basis or specific countries, such as the Yemen situation, due to the differences between the general construction industry and oil and gas industry. Moreover, the factors of these attributes were still accepted due to their applicability to the oil and gas industry, and no significant variances existed between countries. Research has indicated that 51 critical factors cause risks in the oil and gas construction projects in Yemen. Such risk factors can be divided into two major groups: (1) internal risk factors, including seven critical sources of risks, namely client, contractor, consultant, feasibility study and design, tendering and contract, resources and material supply and project management; and (2) external risk factors, including six sources of critical risk factors, namely national economic, political risk, local people, environment and safety, security risk and force-majeure-related risk factors. A risk factor framework was developed to identify the critical risk factors in the oil and gas construction projects in Yemen.Research limitations/implicationsThis research was limited to the oil and gas construction projects.Practical implicationsPractically, this study highlights the risk factors that cause a negative effect on the success of oil and gas construction projects in Yemen. The identification of these factors is the first step in the risk management process to develop strategic responses for risks and enhance the chances of project success.Social implicationsThe identification of risks factors that cause the failure of construction projects helps develop response strategies for these risks, thereby increasing the chances of project success reflected in the oil and gas sector, which is a main tributary of the national economy in developing countries.Originality/valueThis research is the pioneer for future investigations into this vital economic sector. Given the lack of resources and studies in the field of construction projects for the Yemeni oil and gas sector, the Yemeni government, oil companies and researchers in this field are expected to benefit from the results of this study. The critical risk factors specific to the oil and gas construction projects in Yemen should be further investigated with focus only on Yemen and its oil and gas industry players.

scholarly journals Statistical Modeling of RPCA-FCM in Spatiotemporal Rainfall Patterns Recognition

Atmosphere ◽  
2022 ◽  
Vol 13 (1) ◽  
pp. 145
Author(s):  
Siti Mariana Che Mat Nor ◽  
Shazlyn Milleana Shaharudin ◽  
Shuhaida Ismail ◽  
Sumayyah Aimi Mohd Najib ◽  
Mou Leong Tan ◽  
...  
Keyword(s):  
Statistical Modeling ◽  
East Coast ◽  
Monsoon Season ◽  
Clustering Algorithms ◽  
Breakdown Point ◽  
Peninsular Malaysia ◽  
Northeast Monsoon ◽  
Number Of Components ◽  
Torrential Rainfall ◽  
Rainfall Patterns

This study was conducted to identify the spatiotemporal torrential rainfall patterns of the East Coast of Peninsular Malaysia, as it is the region most affected by the torrential rainfall of the Northeast Monsoon season. Dimension reduction, such as the classical Principal Components Analysis (PCA) coupled with the clustering approach, is often applied to reduce the dimension of the data while simultaneously performing cluster partitions. However, the classical PCA is highly insensitive to outliers, as it assigns equal weights to each set of observations. Hence, applying the classical PCA could affect the cluster partitions of the rainfall patterns. Furthermore, traditional clustering algorithms only allow each element to exclusively belong to one cluster, thus observations within overlapping clusters of the torrential rainfall datasets might not be captured effectively. In this study, a statistical model of torrential rainfall pattern recognition was proposed to alleviate these issues. Here, a Robust PCA (RPCA) based on Tukey’s biweight correlation was introduced and the optimum breakdown point to extract the number of components was identified. A breakdown point of 0.4 at 85% cumulative variance percentage efficiently extracted the number of components to avoid low-frequency variations or insignificant clusters on a spatial scale. Based on the extracted components, the rainfall patterns were further characterized based on cluster solutions attained using Fuzzy C-means clustering (FCM) to allow data elements to belong to more than one cluster, as the rainfall data structure permits this. Lastly, data generated using a Monte Carlo simulation were used to evaluate the performance of the proposed statistical modeling. It was found that the proposed RPCA-FCM performed better using RPCA-FCM compared to the classical PCA coupled with FCM in identifying the torrential rainfall patterns of Peninsular Malaysia’s East Coast.

scholarly journals Monsoonal Precipitation Over Peninsular Malaysia in the CMIP6 Highresmip Experiments: The Role of Model Resolution

2021 ◽  
Author(s):  
Ju Liang ◽  
Mou Leong Tan ◽  
Matthew Hawcroft ◽  
Jennifer L. Catto ◽  
Kevin I. Hodges ◽  
...  
Keyword(s):  
Extreme Precipitation ◽  
Monsoon Season ◽  
Southwest Monsoon ◽  
Peninsular Malaysia ◽  
Vertical Resolution ◽  
Model Simulations ◽  
Extreme Precipitation Events ◽  
Different Seasons ◽  
Model Ensembles ◽  
The Impact

Abstract This study investigates the ability of 20 model simulations which contributed to the CMIP6 HighResMIP to simulate precipitation in different monsoon seasons and extreme precipitation events over Peninsular Malaysia. The model experiments utilize common forcing but are run with different horizontal and vertical resolutions. The impact of resolution on the models’ abilities to simulate precipitation and associated environmental fields is assessed by comparing multi-model ensembles at different resolutions with three observed precipitation datasets and four climate reanalyses. Model simulations with relatively high horizontal and vertical resolution exhibit better performance in simulating the annual cycle of precipitation and extreme precipitation over Peninsular Malaysia and the coastal regions. Improvements associated with the increase in horizontal and vertical resolutions are also found in the statistical relationship between precipitation and monsoon intensity in different seasons. However, the increase in vertical resolution can lead to a reduction of annual mean precipitation compared to that from the models with low vertical resolutions, associated with an overestimation of moisture divergence and underestimation of lower-tropospheric vertical ascent in the different monsoon seasons. This limits any improvement in the simulation of precipitation in the high vertical resolution experiments, particularly for the Southwest monsoon season.

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