The Experts below are selected from a list of 120 Experts worldwide ranked by ideXlab platform
Bryant W Bradley - One of the best experts on this subject based on the ideXlab platform.
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Application of Production Decline Curve Analysis to Clastic Reservoir Facies Characterization within a Sequence Stratigraphic Framework: Example—Frio Formation, South Texas
2020Co-Authors: John D Pigott, Bryant W BradleyAbstract:Abstract Viewed within a dynamic 3D accommodation perspective, petrophysical log motifs of 113 wells in the adjoining Captain Lucey and Richard King fields of Jim Wells and Nueces counties, South Texas, reveal the overprint of fourth-order autocyclic processes of regression and transgression within a general third-order allocyclic sea level fall. Five reservoir sand environmental assemblages sealed by transgressive systems tract (TST) shales identified within the clastic shelf wedge of the Oligocene-Miocene Frio Formation are: lowstand systems tract (LST) delta 1, regressive systems tract (RST) to LST delta plain distributaries, RST–LST distributary crevasse splay, TST barrier island, and LST–RST delta 2. Production Decline Curve analysis (PDCA) of 18 reservoirs in 12 of 20 currently active wells of these two fields demonstrate a systematic relationship between reservoir elements and their associated depositional environments. The deltaic 1 and deltaic 2 environments (delta front sands) have the best reservoir quality sands of the five, exhibiting linear lowest Decline rates with the highest average flow permeabilities (80 md) and largest drainage areas (290 ac). A close second in drainage area (214 ac) is the barrier island sand with lower average flow permeability (7 md). The fluvial sand exhibits the highest Decline rates with good drainage area (214 ac) and modest average permeability (32 md). The poorest reservoir quality is the crevasse splay sand with rapidly declining rates, lowest average permeability (1 md) and smallest drainage area (110 ac). The strong relationships between PDCA and depositional environments in these South Texas Frio Formation sands point to the potential applicability of PDCA—depositional facies linkages as a reservoir performance predictor in fields elsewhere.
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application of Production Decline Curve analysis to clastic reservoir facies characterization within a sequence stratigraphic framework example frio formation south texas
2014Co-Authors: John D Pigott, Bryant W BradleyAbstract:Abstract Viewed within a dynamic 3D accommodation perspective, petrophysical log motifs of 113 wells in the adjoining Captain Lucey and Richard King fields of Jim Wells and Nueces counties, South Texas, reveal the overprint of fourth-order autocyclic processes of regression and transgression within a general third-order allocyclic sea level fall. Five reservoir sand environmental assemblages sealed by transgressive systems tract (TST) shales identified within the clastic shelf wedge of the Oligocene-Miocene Frio Formation are: lowstand systems tract (LST) delta 1, regressive systems tract (RST) to LST delta plain distributaries, RST–LST distributary crevasse splay, TST barrier island, and LST–RST delta 2. Production Decline Curve analysis (PDCA) of 18 reservoirs in 12 of 20 currently active wells of these two fields demonstrate a systematic relationship between reservoir elements and their associated depositional environments. The deltaic 1 and deltaic 2 environments (delta front sands) have the best reservoir quality sands of the five, exhibiting linear lowest Decline rates with the highest average flow permeabilities (80 md) and largest drainage areas (290 ac). A close second in drainage area (214 ac) is the barrier island sand with lower average flow permeability (7 md). The fluvial sand exhibits the highest Decline rates with good drainage area (214 ac) and modest average permeability (32 md). The poorest reservoir quality is the crevasse splay sand with rapidly declining rates, lowest average permeability (1 md) and smallest drainage area (110 ac). The strong relationships between PDCA and depositional environments in these South Texas Frio Formation sands point to the potential applicability of PDCA—depositional facies linkages as a reservoir performance predictor in fields elsewhere.
Zhang Ji-cheng - One of the best experts on this subject based on the ideXlab platform.
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Analysis of Development Characteristics and Prediction of Oil Recovery Factor of Lianhua Oil-layer in Qi 3-17-5 Block
Science Technology and Engineering, 2020Co-Authors: Zhang Ji-chengAbstract:After thirty years of development in Lianhua oil-layer,it has entered into the stage of low speed development with an oil Production rate of 0.033%.It firstly divides the development period of Lianhua oil-layer into different phases and analyzes the development characteristics in every phase.Then predict the oil recovery factor by using the Production-Decline Curve method to estimate the final recoverable reserves and recovery percent of reserves.Results show that,the final recoverable reserves of Lianhua oil-layer is about 50.813×104 t,and the oil recovery factor is 13.177%.At present,recovery percent of recoverable reserves has been 95.094% that the remaining recoverable reserves are in the least.Therefore,it urgently needs to find a more reasonable development model to do secondary development of Lianhua oil-layer.The conclusions have an important realistic significance of guiding the Lianhua oil-layer to do secondary development.
Mikael Höök - One of the best experts on this subject based on the ideXlab platform.
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Production Decline Curves of Tight Oil Wells in Eagle Ford Shale
Natural Resources Research, 2017Co-Authors: Henrik Wachtmeister, Linnea Lund, Kjell Aleklett, Mikael HöökAbstract:This study derives typical Production Curves of tight oil wells based on monthly Production data from multiple horizontal Eagle Ford shale oil wells. Well properties initial Production (IP) rate and Production Decline rate were documented, and estimated ultimate recovery (EUR) was calculated using two empirical Production Decline Curve models, the hyperbolic and the stretched exponential function. Individual well productivity, which can be described by IP level, Production Decline curvature and well lifetime, varies significantly. The average monthly IP was found to be around 500 bbl/day, which yields an EUR in the range of 150–290 kbbl depending on used Curve, assumed well lifetime or Production cutoff level. More detailed analyses on EUR can be made once longer time series are available. For more realistic modeling of multiple wells a probabilistic approach might be favorable to account for variety in well productivity. For less detailed modeling, for example conceptual regional bottom-up Production modeling, the hyperbolic function with deterministic parameters might be preferred because of ease of use, for example with the average parameter values IP = 500 bbl/day, D = 0.3 and b = 1 resulting in an EUR of 250 kbbl with a 30-year well lifetime, however, with the recognition that this extrapolation is uncertain.
John D Pigott - One of the best experts on this subject based on the ideXlab platform.
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Application of Production Decline Curve Analysis to Clastic Reservoir Facies Characterization within a Sequence Stratigraphic Framework: Example—Frio Formation, South Texas
2020Co-Authors: John D Pigott, Bryant W BradleyAbstract:Abstract Viewed within a dynamic 3D accommodation perspective, petrophysical log motifs of 113 wells in the adjoining Captain Lucey and Richard King fields of Jim Wells and Nueces counties, South Texas, reveal the overprint of fourth-order autocyclic processes of regression and transgression within a general third-order allocyclic sea level fall. Five reservoir sand environmental assemblages sealed by transgressive systems tract (TST) shales identified within the clastic shelf wedge of the Oligocene-Miocene Frio Formation are: lowstand systems tract (LST) delta 1, regressive systems tract (RST) to LST delta plain distributaries, RST–LST distributary crevasse splay, TST barrier island, and LST–RST delta 2. Production Decline Curve analysis (PDCA) of 18 reservoirs in 12 of 20 currently active wells of these two fields demonstrate a systematic relationship between reservoir elements and their associated depositional environments. The deltaic 1 and deltaic 2 environments (delta front sands) have the best reservoir quality sands of the five, exhibiting linear lowest Decline rates with the highest average flow permeabilities (80 md) and largest drainage areas (290 ac). A close second in drainage area (214 ac) is the barrier island sand with lower average flow permeability (7 md). The fluvial sand exhibits the highest Decline rates with good drainage area (214 ac) and modest average permeability (32 md). The poorest reservoir quality is the crevasse splay sand with rapidly declining rates, lowest average permeability (1 md) and smallest drainage area (110 ac). The strong relationships between PDCA and depositional environments in these South Texas Frio Formation sands point to the potential applicability of PDCA—depositional facies linkages as a reservoir performance predictor in fields elsewhere.
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application of Production Decline Curve analysis to clastic reservoir facies characterization within a sequence stratigraphic framework example frio formation south texas
2014Co-Authors: John D Pigott, Bryant W BradleyAbstract:Abstract Viewed within a dynamic 3D accommodation perspective, petrophysical log motifs of 113 wells in the adjoining Captain Lucey and Richard King fields of Jim Wells and Nueces counties, South Texas, reveal the overprint of fourth-order autocyclic processes of regression and transgression within a general third-order allocyclic sea level fall. Five reservoir sand environmental assemblages sealed by transgressive systems tract (TST) shales identified within the clastic shelf wedge of the Oligocene-Miocene Frio Formation are: lowstand systems tract (LST) delta 1, regressive systems tract (RST) to LST delta plain distributaries, RST–LST distributary crevasse splay, TST barrier island, and LST–RST delta 2. Production Decline Curve analysis (PDCA) of 18 reservoirs in 12 of 20 currently active wells of these two fields demonstrate a systematic relationship between reservoir elements and their associated depositional environments. The deltaic 1 and deltaic 2 environments (delta front sands) have the best reservoir quality sands of the five, exhibiting linear lowest Decline rates with the highest average flow permeabilities (80 md) and largest drainage areas (290 ac). A close second in drainage area (214 ac) is the barrier island sand with lower average flow permeability (7 md). The fluvial sand exhibits the highest Decline rates with good drainage area (214 ac) and modest average permeability (32 md). The poorest reservoir quality is the crevasse splay sand with rapidly declining rates, lowest average permeability (1 md) and smallest drainage area (110 ac). The strong relationships between PDCA and depositional environments in these South Texas Frio Formation sands point to the potential applicability of PDCA—depositional facies linkages as a reservoir performance predictor in fields elsewhere.
Henrik Wachtmeister - One of the best experts on this subject based on the ideXlab platform.
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Production Decline Curves of Tight Oil Wells in Eagle Ford Shale
Natural Resources Research, 2017Co-Authors: Henrik Wachtmeister, Linnea Lund, Kjell Aleklett, Mikael HöökAbstract:This study derives typical Production Curves of tight oil wells based on monthly Production data from multiple horizontal Eagle Ford shale oil wells. Well properties initial Production (IP) rate and Production Decline rate were documented, and estimated ultimate recovery (EUR) was calculated using two empirical Production Decline Curve models, the hyperbolic and the stretched exponential function. Individual well productivity, which can be described by IP level, Production Decline curvature and well lifetime, varies significantly. The average monthly IP was found to be around 500 bbl/day, which yields an EUR in the range of 150–290 kbbl depending on used Curve, assumed well lifetime or Production cutoff level. More detailed analyses on EUR can be made once longer time series are available. For more realistic modeling of multiple wells a probabilistic approach might be favorable to account for variety in well productivity. For less detailed modeling, for example conceptual regional bottom-up Production modeling, the hyperbolic function with deterministic parameters might be preferred because of ease of use, for example with the average parameter values IP = 500 bbl/day, D = 0.3 and b = 1 resulting in an EUR of 250 kbbl with a 30-year well lifetime, however, with the recognition that this extrapolation is uncertain.
