The Experts below are selected from a list of 321 Experts worldwide ranked by ideXlab platform
A K Permadi - One of the best experts on this subject based on the ideXlab platform.
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ROBUST DECLINE Curve Analysis
Journal of the Indonesian Mathematical Society, 2012Co-Authors: Sutawanir Darwis, Budi Nurani Ruchjana, A K PermadiAbstract:Empirical decline Curve Analysis of oil production data gives reasonable answer in hyperbolic type Curves situations; however the methodology has limitations in fitting real historical production data in present of unusual observations due to the effect of the treatment to the well in order to increase production capacity. The development ofrobust least squares offers new possibilities in better fitting production data using declineCurve Analysis by down weighting the unusual observations. This paper proposes a robustleast squares fitting lmRobMM approach to estimate the decline rate of daily production data and compares the results with reservoir simulation results. For case study, we usethe oil production data at TBA Field West Java. The results demonstrated that theapproach is suitable for decline Curve fitting and offers a new insight in decline Curve Analysis in the present of unusual observations. DOI : http://dx.doi.org/10.22342/jims.15.2.50.105-111
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robust decline Curve Analysis
Journal of the Indonesian Mathematical Society, 2012Co-Authors: Sutawanir Darwis, Budi Nurani Ruchjana, A K PermadiAbstract:Empirical decline Curve Analysis of oil production data gives reasonable answer in hyperbolic type Curves situations; however the methodology has limitations in fitting real historical production data in present of unusual observations due to the effect of the treatment to the well in order to increase production capacity. The development ofrobust least squares offers new possibilities in better fitting production data using declineCurve Analysis by down weighting the unusual observations. This paper proposes a robustleast squares fitting lmRobMM approach to estimate the decline rate of daily production data and compares the results with reservoir simulation results. For case study, we usethe oil production data at TBA Field West Java. The results demonstrated that theapproach is suitable for decline Curve fitting and offers a new insight in decline Curve Analysis in the present of unusual observations. DOI : http://dx.doi.org/10.22342/jims.15.2.50.105-111
Binbin Wang - One of the best experts on this subject based on the ideXlab platform.
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methods of decline Curve Analysis for shale gas reservoirs
Energies, 2018Co-Authors: Binbin WangAbstract:With help from horizontal wells and hydraulic fracturing, shale gas has made a significant contribution to the energy supply. However, due to complex fracture networks and complicated mechanisms such as gas desorption and gas slippage in shale, forecasting shale gas production is a challenging task. Despite the versatility of many simulation methods including analytical models, semi-analytical models, and numerical simulation, Decline Curve Analysis has the advantages of simplicity and efficiency for hydrocarbon production forecasting. In this article, the eight most popular deterministic decline Curve methods are reviewed: Arps, Logistic Growth Model, Power Law Exponential Model, Stretched Exponential Model, Duong Model, Extended Exponential Decline Model, and Fractural Decline Curve model. This review article is dedicated to summarizing the origins, derivations, assumptions, and limitations of these eight decline Curve models. This review article also describes the current status of decline Curve Analysis methods, which provides a comprehensive and up-to-date list of Decline Curve Analysis models for petroleum engineers in Analysis of shale gas reservoirs. This work could serve as a guideline for petroleum engineers to determine which Decline Curve models should be applied to different shale gas fields and production periods.
Sutawanir Darwis - One of the best experts on this subject based on the ideXlab platform.
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ROBUST DECLINE Curve Analysis
Journal of the Indonesian Mathematical Society, 2012Co-Authors: Sutawanir Darwis, Budi Nurani Ruchjana, A K PermadiAbstract:Empirical decline Curve Analysis of oil production data gives reasonable answer in hyperbolic type Curves situations; however the methodology has limitations in fitting real historical production data in present of unusual observations due to the effect of the treatment to the well in order to increase production capacity. The development ofrobust least squares offers new possibilities in better fitting production data using declineCurve Analysis by down weighting the unusual observations. This paper proposes a robustleast squares fitting lmRobMM approach to estimate the decline rate of daily production data and compares the results with reservoir simulation results. For case study, we usethe oil production data at TBA Field West Java. The results demonstrated that theapproach is suitable for decline Curve fitting and offers a new insight in decline Curve Analysis in the present of unusual observations. DOI : http://dx.doi.org/10.22342/jims.15.2.50.105-111
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robust decline Curve Analysis
Journal of the Indonesian Mathematical Society, 2012Co-Authors: Sutawanir Darwis, Budi Nurani Ruchjana, A K PermadiAbstract:Empirical decline Curve Analysis of oil production data gives reasonable answer in hyperbolic type Curves situations; however the methodology has limitations in fitting real historical production data in present of unusual observations due to the effect of the treatment to the well in order to increase production capacity. The development ofrobust least squares offers new possibilities in better fitting production data using declineCurve Analysis by down weighting the unusual observations. This paper proposes a robustleast squares fitting lmRobMM approach to estimate the decline rate of daily production data and compares the results with reservoir simulation results. For case study, we usethe oil production data at TBA Field West Java. The results demonstrated that theapproach is suitable for decline Curve fitting and offers a new insight in decline Curve Analysis in the present of unusual observations. DOI : http://dx.doi.org/10.22342/jims.15.2.50.105-111
Budi Nurani Ruchjana - One of the best experts on this subject based on the ideXlab platform.
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ROBUST DECLINE Curve Analysis
Journal of the Indonesian Mathematical Society, 2012Co-Authors: Sutawanir Darwis, Budi Nurani Ruchjana, A K PermadiAbstract:Empirical decline Curve Analysis of oil production data gives reasonable answer in hyperbolic type Curves situations; however the methodology has limitations in fitting real historical production data in present of unusual observations due to the effect of the treatment to the well in order to increase production capacity. The development ofrobust least squares offers new possibilities in better fitting production data using declineCurve Analysis by down weighting the unusual observations. This paper proposes a robustleast squares fitting lmRobMM approach to estimate the decline rate of daily production data and compares the results with reservoir simulation results. For case study, we usethe oil production data at TBA Field West Java. The results demonstrated that theapproach is suitable for decline Curve fitting and offers a new insight in decline Curve Analysis in the present of unusual observations. DOI : http://dx.doi.org/10.22342/jims.15.2.50.105-111
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robust decline Curve Analysis
Journal of the Indonesian Mathematical Society, 2012Co-Authors: Sutawanir Darwis, Budi Nurani Ruchjana, A K PermadiAbstract:Empirical decline Curve Analysis of oil production data gives reasonable answer in hyperbolic type Curves situations; however the methodology has limitations in fitting real historical production data in present of unusual observations due to the effect of the treatment to the well in order to increase production capacity. The development ofrobust least squares offers new possibilities in better fitting production data using declineCurve Analysis by down weighting the unusual observations. This paper proposes a robustleast squares fitting lmRobMM approach to estimate the decline rate of daily production data and compares the results with reservoir simulation results. For case study, we usethe oil production data at TBA Field West Java. The results demonstrated that theapproach is suitable for decline Curve fitting and offers a new insight in decline Curve Analysis in the present of unusual observations. DOI : http://dx.doi.org/10.22342/jims.15.2.50.105-111
Chen Yu-nin - One of the best experts on this subject based on the ideXlab platform.
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Genotyping of platelet antigens HPA-2 with melting Curve Analysis
Chinese Journal of Public Health, 2013Co-Authors: Chen Yu-ninAbstract:Objective To develop a genotyping method for human platelet antigens-2(HPA-2) by using melting Curve Analysis and to investigate the gene frequencies of HPA-2 in Han population in Dalian city. Methods Real-time PCR was used and melting Curve Analysis was performed for genotyping of HPA-2. Reproducibility of the method was evaluated and the results of melting Curve Analysis were compared with those using traditional PCR amplification with sequence-specific primers(PCR-SSP) method. The genotype of HPA-2 in 155 Han platelet donors were determined using melting Curve Analysis,then the gene frequencies of HPA-2 were compared with that of other populations in China Results Melting Curve of HPA-2aa sample showed a single peak with the melting temperature(Tm) of 85 ± 1 ℃; melting Curve of HPA-2ab sample showed two peaks with the Tm of 80 ± 1 ℃ and 85 ± 1 ℃; and melting Curve of HPA-2bb sample showed a single peak,with the Tm of 80 ± 1 ℃. There was complete concordance of results for all samples tested by PCR-SSP and melting Curve Analysis. The gene frequencies of HPA-2a and HPA-2b in Han populations of Dalian city were 0. 9161 and 0. 0838,respectively. The distribution of HPA-2 alleles in Liaoning Han populations is similar to that in Nanjing,Shanghai,and Xinjiang Han and Xingjiang Uyghur populations(P 0. 05 for all),but it significantly differ from that in Hainan Li national minority people(P 0. 05). Conclusion The method for genotyping of HPA-2 by using melting Curve Analysis was developed and the method is faster,simpler,and more accurate compared to the results of traditional PCR-SSP. There are differences in HPA-2 genotypes among different race in China
