M. H. Yusof, M. Z. Sulaiman, Rahimah A. Halim, Nurfaridah Bt Ahmad Fauzi, Ahgheelan Sella Thurai, Masseera Mahictin, Tg Zuhaili Tg Yahya, Fadli Adlan Muslim
{"title":"Delivering Low Cost Wells at Matured Field with Enhanced Statistical Approach","authors":"M. H. Yusof, M. Z. Sulaiman, Rahimah A. Halim, Nurfaridah Bt Ahmad Fauzi, Ahgheelan Sella Thurai, Masseera Mahictin, Tg Zuhaili Tg Yahya, Fadli Adlan Muslim","doi":"10.4043/30994-ms","DOIUrl":null,"url":null,"abstract":"\n This paper discusses the Case study of Field A in offshore Sarawak, Malaysia which focus on re-thinking development based on statistical analysis of the fields. Conventionally, well design is driven by subsurface requirement by targeting the high-reserve sand and well is designed to meet subsurface objectives. However, the conventional way may not be efficient to develop matured field environment due to the high CAPEX and the inconsistencies among well design especially in current volatile oil price period. The objective of this fit-for-purpose approach which is called \"Cone Concept Statistical Approach\" is to steer away from the conventional way of targeting only sweet spots whilst leaving the remaining potential resources undeveloped. Based on the statistical analysis and subsurface fields pattern, the \"Cone Concept Statistical Approach\" in which standardizing well design and trajectories was developed to extract the whole fields’ reserve at maximum. Well design boundaries were introduced to ensure this approach can be replicated throughout the field. Not only this study covers drilling perspective, completion perspective was also taken into consideration by exploring a cheaper and fit for purpose sand control method, considering it is a matured field with relatively short remaining field life. The Well Cost Catalogue for this field-specific was also developed which contains different types of design and completion, in order to holistically evaluate sand control method and identify the best option for the project moving forward.\n This \"Cone Concept Statistical Approach\" aims to enable operator to drill more simple wells within the same allocated budget in which poses low-to-none risk in the design and execution phase, promoting learning curve to improve operation & HSE, and ultimately to get positive project economics. Since this simple approach can be implemented early on even during the pre-FEL stage, the FDP team & host authority can come together to jointly discuss the targets/platform ranking and segregate them into various phases. Hence, the number of platforms or drilling centers, and its location also can be optimized early on with this concept, and again, translating into further reduction in overall project cost. This paper will help other operators and host authority to understand better on how a specific development concept on statistical approach can result and turn the matured-challenging fields into more economically attractive projects – low overall development cost and maximizing the recovery.","PeriodicalId":11072,"journal":{"name":"Day 1 Mon, August 16, 2021","volume":"7 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Day 1 Mon, August 16, 2021","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4043/30994-ms","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper discusses the Case study of Field A in offshore Sarawak, Malaysia which focus on re-thinking development based on statistical analysis of the fields. Conventionally, well design is driven by subsurface requirement by targeting the high-reserve sand and well is designed to meet subsurface objectives. However, the conventional way may not be efficient to develop matured field environment due to the high CAPEX and the inconsistencies among well design especially in current volatile oil price period. The objective of this fit-for-purpose approach which is called "Cone Concept Statistical Approach" is to steer away from the conventional way of targeting only sweet spots whilst leaving the remaining potential resources undeveloped. Based on the statistical analysis and subsurface fields pattern, the "Cone Concept Statistical Approach" in which standardizing well design and trajectories was developed to extract the whole fields’ reserve at maximum. Well design boundaries were introduced to ensure this approach can be replicated throughout the field. Not only this study covers drilling perspective, completion perspective was also taken into consideration by exploring a cheaper and fit for purpose sand control method, considering it is a matured field with relatively short remaining field life. The Well Cost Catalogue for this field-specific was also developed which contains different types of design and completion, in order to holistically evaluate sand control method and identify the best option for the project moving forward.
This "Cone Concept Statistical Approach" aims to enable operator to drill more simple wells within the same allocated budget in which poses low-to-none risk in the design and execution phase, promoting learning curve to improve operation & HSE, and ultimately to get positive project economics. Since this simple approach can be implemented early on even during the pre-FEL stage, the FDP team & host authority can come together to jointly discuss the targets/platform ranking and segregate them into various phases. Hence, the number of platforms or drilling centers, and its location also can be optimized early on with this concept, and again, translating into further reduction in overall project cost. This paper will help other operators and host authority to understand better on how a specific development concept on statistical approach can result and turn the matured-challenging fields into more economically attractive projects – low overall development cost and maximizing the recovery.