A. Jaja, Nnamdi Okani, Vincent Eme, Ricardo Combella Ricardos, Chevron Gom, Lynn Silpngarmlers
{"title":"基于油藏不确定性特征的成熟油藏综合研究创造价值——以尼日尔三角洲油田A05油藏为例","authors":"A. Jaja, Nnamdi Okani, Vincent Eme, Ricardo Combella Ricardos, Chevron Gom, Lynn Silpngarmlers","doi":"10.2118/198822-MS","DOIUrl":null,"url":null,"abstract":"\n In the Early phases of field development, the drilled hydrocarbon appraisal wells may not have been sufficient to define rock properties, fluid typing and contacts. It's very important to define the range of uncertainty in such fields. This is because as the field matures other dynamic data will become available to validate these probable volumes.\n The ideal development scenario provides the practitioner with a full suite of data defining the reservoir geometries, reservoir properties, fluid properties etc. to make subsurface decisions. However, in most cases, operational realities will deny the reservoir practitioner this full suite of data.\n One practical convention that is used to resolve this data paucity challenge is to evaluate and report the lowest possible volume, if this low case is economic the project will be economic with potential for more upside outcomes. However, a challenge that can arise with this is that after several iterations the low case can become the only case. A better practice is to characterize uncertainty of reservoir parameters during the early stages of field development and carry out the full range outcomes through the field's life. These ranges will then be validated as the field matures.\n This paper demonstrates a case in the Niger Delta field A05 reservoir were dynamic simulation model was used to narrow the uncertainty range on the GOC. Proper identification and characterization of the GOC uncertainties helped for the estimate of a range of STOOIP used for dynamic simulation model. Though no static dataset was available to reduce this uncertainty on the GOC, during dynamic simulation, the high-case oil in-place volume was found to be the best match to historical production data with the integration of another reservoir, Delta A12, in one dynamic simulation model. Both reservoirs communicate through the aquifer, separated by a saddle. This then proved up additional volumes in the reservoir, identified previously overlooked reserves and allowed the asset team to propose an extra infill well opportunity than what was previously planned. This new understanding of the A05 reservoir increased the oil estimated ultimate recovery (EUR) by 4.6 MMSTBO.","PeriodicalId":11110,"journal":{"name":"Day 2 Tue, August 06, 2019","volume":"5 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Creating Value Through Integrated Reservoir Study in Mature Asset via Reservoir Uncertainty Characterization: A Case Study from the Niger Delta Field A05 Reservoir\",\"authors\":\"A. Jaja, Nnamdi Okani, Vincent Eme, Ricardo Combella Ricardos, Chevron Gom, Lynn Silpngarmlers\",\"doi\":\"10.2118/198822-MS\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n In the Early phases of field development, the drilled hydrocarbon appraisal wells may not have been sufficient to define rock properties, fluid typing and contacts. It's very important to define the range of uncertainty in such fields. This is because as the field matures other dynamic data will become available to validate these probable volumes.\\n The ideal development scenario provides the practitioner with a full suite of data defining the reservoir geometries, reservoir properties, fluid properties etc. to make subsurface decisions. However, in most cases, operational realities will deny the reservoir practitioner this full suite of data.\\n One practical convention that is used to resolve this data paucity challenge is to evaluate and report the lowest possible volume, if this low case is economic the project will be economic with potential for more upside outcomes. However, a challenge that can arise with this is that after several iterations the low case can become the only case. A better practice is to characterize uncertainty of reservoir parameters during the early stages of field development and carry out the full range outcomes through the field's life. These ranges will then be validated as the field matures.\\n This paper demonstrates a case in the Niger Delta field A05 reservoir were dynamic simulation model was used to narrow the uncertainty range on the GOC. Proper identification and characterization of the GOC uncertainties helped for the estimate of a range of STOOIP used for dynamic simulation model. Though no static dataset was available to reduce this uncertainty on the GOC, during dynamic simulation, the high-case oil in-place volume was found to be the best match to historical production data with the integration of another reservoir, Delta A12, in one dynamic simulation model. Both reservoirs communicate through the aquifer, separated by a saddle. This then proved up additional volumes in the reservoir, identified previously overlooked reserves and allowed the asset team to propose an extra infill well opportunity than what was previously planned. 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Creating Value Through Integrated Reservoir Study in Mature Asset via Reservoir Uncertainty Characterization: A Case Study from the Niger Delta Field A05 Reservoir
In the Early phases of field development, the drilled hydrocarbon appraisal wells may not have been sufficient to define rock properties, fluid typing and contacts. It's very important to define the range of uncertainty in such fields. This is because as the field matures other dynamic data will become available to validate these probable volumes.
The ideal development scenario provides the practitioner with a full suite of data defining the reservoir geometries, reservoir properties, fluid properties etc. to make subsurface decisions. However, in most cases, operational realities will deny the reservoir practitioner this full suite of data.
One practical convention that is used to resolve this data paucity challenge is to evaluate and report the lowest possible volume, if this low case is economic the project will be economic with potential for more upside outcomes. However, a challenge that can arise with this is that after several iterations the low case can become the only case. A better practice is to characterize uncertainty of reservoir parameters during the early stages of field development and carry out the full range outcomes through the field's life. These ranges will then be validated as the field matures.
This paper demonstrates a case in the Niger Delta field A05 reservoir were dynamic simulation model was used to narrow the uncertainty range on the GOC. Proper identification and characterization of the GOC uncertainties helped for the estimate of a range of STOOIP used for dynamic simulation model. Though no static dataset was available to reduce this uncertainty on the GOC, during dynamic simulation, the high-case oil in-place volume was found to be the best match to historical production data with the integration of another reservoir, Delta A12, in one dynamic simulation model. Both reservoirs communicate through the aquifer, separated by a saddle. This then proved up additional volumes in the reservoir, identified previously overlooked reserves and allowed the asset team to propose an extra infill well opportunity than what was previously planned. This new understanding of the A05 reservoir increased the oil estimated ultimate recovery (EUR) by 4.6 MMSTBO.