ORCID Profile
0000-0001-7938-7022
Current Organisation
University of Adelaide
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Publisher: Elsevier BV
Date: 12-2013
Publisher: Elsevier BV
Date: 04-2016
Publisher: Elsevier BV
Date: 06-2015
Publisher: Elsevier BV
Date: 10-2017
Publisher: Elsevier BV
Date: 02-2013
Publisher: Elsevier BV
Date: 10-2022
Publisher: Elsevier BV
Date: 10-2015
Publisher: Elsevier BV
Date: 11-2014
Publisher: Elsevier BV
Date: 06-2017
Publisher: Wiley
Date: 21-09-2014
DOI: 10.1002/CJCE.22044
Publisher: EDP Sciences
Date: 2018
DOI: 10.2516/OGST/2018037
Abstract: Nowadays, incredible growth of the energy consumption has changed the global attention to the production and utilization of the heavy crude oils such as bitumen resources around the globe. Amongst the bitumen properties, density is an important parameter which improves bitumen recovery efficiency and transportation quality. For easy production of bitumen, n -alkanes are usually injected into the reservoir to reduce its viscosity and density however, there are few numbers of models focusing on proper estimation rediction of diluted bitumen mixture density in literature. In present work, a new method was proposed to accurately prognosticate the bitumen/ n -tetradecane mixture density as a function of thermodynamic conditions using Gene Expression Programming (GEP) for the first time as a function of solvent composition, pressure and temperature. Consequently, the proposed model here predicts the mixture density with the average Absolute Relative Deviation (AARD%) of 0.3016% and R -squared ( R 2 ) of 0.9943. Moreover, it is found out the solvent concentration has the highest impact value on mixture density estimation. In conclusion, results of the present study can be so valuable for field engineers and researchers working on solvent-assisted recovery methods from heavy oil reservoirs.
Publisher: Informa UK Limited
Date: 27-06-2014
Publisher: Elsevier BV
Date: 11-2013
Publisher: CSIRO Publishing
Date: 11-05-2023
DOI: 10.1071/AJ22191
Abstract: Identifying potential petroleum traps in petroleum basins is one of the key challenges in petroleum exploration. Specifically, it is the identification of probable petroleum traps within a set of stratigraphic traps of a particular location of source rock and carrier bed. One solution lies in understanding the behaviour of hydrocarbon flow during secondary migration, and the evaluation of the probability of successful transport from the source rock to the trap. Modern reservoir simulators rely on numerical methods to model the oil/gas secondary migration. Using numerical simulators is, however, cumbersome and requires high volumes of data and computation time, which affects successful decision-making in exploration planning. Yet, analytical models are fast and allow for multivariant analysis of hydrocarbon secondary migration requiring only a moderate amount of geological data. This study presents the analytical modelling of hydrocarbon buoyant transport in petroleum basins by including the (i) areal variation of stringers’ cross-section, (ii) chemical reactions including oil biodegradation and (iii) hydrological water flow. The explicit formula is provided for the first and last moments of hydrocarbon arrival at the trap, describing the dynamics of filling of the trap. Field data from Australian and Chinese basins are used to investigate the effects of the above-mentioned parameters on the first and last moments of hydrocarbon arrival at the trap.
Publisher: Elsevier BV
Date: 07-2014
Publisher: Oxford University Press (OUP)
Date: 05-02-2015
Publisher: Elsevier BV
Date: 11-2015
Publisher: Elsevier BV
Date: 10-2013
Publisher: Wiley
Date: 29-11-2018
DOI: 10.1002/EP.13089
Publisher: Elsevier BV
Date: 08-2015
Publisher: American Chemical Society (ACS)
Date: 25-07-0088
DOI: 10.1021/IE4013908
Publisher: EDP Sciences
Date: 2019
DOI: 10.2516/OGST/2019032
Abstract: Mineral scaling has been considered a great concern for developing the oil production from the underground petroleum reservoirs. One of the main causes of this phenomenon is known as the chemical incompatibility of injected brine, frequently sea water, with the reservoir brine leading to the deposition of various supersaturated salts such as calcium carbonate, calcium sulfate and barium sulfate. In present communication, an evolutionary approach namely, Gene Expression Programming (GEP), was employed for rigorous modeling of formation damage by mineral scaling of mixed sulfate salt deposition. At first, a large databank of damaged permeability datapoints as a function of injected volume, injection flowrate, temperature, differential pressure and ionic concentrations of the existing chemical species in the porous media was employed. In this regard, a user-friendly correlation was extended for the first time by the aforementioned technique in the literature. Professional evaluation of the suggested GEP-based model was implemented by different statistical parameters and appealing visualization tools. Having proposed the GEP-based correlation, statistical parameters of the Average Absolute Relative Deviation Percent (AARD%) of 0.640% and determination coefficient ( R 2 ) of 0.984 was calculated. Accordingly, it is demonstrated that the proposed model has a superior performance and great potential for efficient prediction of damaged permeability due to the mixed sulfate salt scaling. Moreover, the implemented outlier diagnosis technique verified the validity of the databank used for modeling, as well as the high robustness of the suggested model was confirmed. In conclusion, the developed correlation in this work can be of enormous practical value for skillful engineers and scientists in any academic study and industrial applications dealing with mixed salt deposition.
Publisher: Wiley
Date: 17-07-2015
DOI: 10.1002/CJCE.22257
Publisher: Elsevier BV
Date: 12-2015
Publisher: Elsevier BV
Date: 2016
Publisher: Elsevier BV
Date: 09-2014
Publisher: Elsevier BV
Date: 05-2014
Publisher: Elsevier BV
Date: 04-2015
Publisher: Elsevier BV
Date: 07-2017
Publisher: American Chemical Society (ACS)
Date: 24-12-2013
DOI: 10.1021/IE402829P
Publisher: Elsevier BV
Date: 2014
Publisher: Elsevier BV
Date: 05-2023
Publisher: Informa UK Limited
Date: 14-05-2014
Publisher: Elsevier BV
Date: 07-2023
Publisher: Elsevier BV
Date: 12-2017
Location: Iran (Islamic Republic of)
No related grants have been discovered for Amin Shokrollahi.