Search

Your search keyword '"Sadri, Mahdi"' showing total 17 results
Start Over Author "Sadri, Mahdi"
17 results on '"Sadri, Mahdi"'

2. Improving the economic recovery of oil and gas through data analysis and optimal flow measurement

Author

Sadri, Mahdi, Shariatipour, Seyed, Hunt, Andrew, Gaura, Elena, and Henry, Manus

Subjects
338.2, oil and gas, data analysis, flow measurement, reservoir management, allocation, machine learning, artificial neural network, reservoir simulation, modelling, uncertainty, hydrocarbon accounting, history matching, well testing
Abstract

Although our energy supply is not longed purely wedded to fossil fuels but produced from a wider range of sources such as solar or wind these days, there remains a considerable challenge in providing affordable and reliable energy to all households around the world. The oil and gas industry as the biggest supplier to address this demand for energy still plays the major role in the energy market and has an extensive influence on the energy price. Increasing the economic efficiency of the processes and the energy-producing systems in this industry can therefore significantly contribute to securing energy affordability. With the ever-increasing application of data in the oil and gas industry, its availability and accuracy are of vital importance in hydrocarbon field management and increasing the economic recovery of oil and gas. Perhaps the most important type of data in the oil and gas industry are production flow rates which is a basis of decisions in hydrocarbon field management. In many cases, however, the production data of wells contain large flow measurement uncertainties or are not available continuously due to the shortcomings of the traditional methods of flow measurement or estimation that are still used in the industry. This research has investigated the effects of these uncertainties on the economic recovery of oil and gas reservoirs and tried to propose solutions for mitigating them. In order to do that, the uncertainties in the production data have been statistically analysed and the effects of the frequency of flow tests on the accuracy of allocation calculations and hydrocarbon accounting have been investigated (Chapter 3). The case studies in the analysis showed up to 80 million dollars reduction in the annual cost of allocation uncertainties when flow tests were undertaken weekly instead of monthly in an oil field with 36 production wells. Based on the statistical analysis, a method that includes the application of an artificial neural network has been proposed to find the minimum frequency of flow tests required to achieve a desired allocation error (Chapter 4). The effects of the uncertainties of flow data on history matching and well testing (Chapter 5), which are two main exercises contributing to reservoir management, have been investigated subsequently. The results show the significance of the negative effect of systematic errors and therefore the importance of regular calibration and maintenance of flow meters, installing multi-phase flow meters on individual wells, and recording the data downhole instead of on the surface.

Published
2020

9. Uncertainty Quantification of the CO 2 Storage Process in the Bunter Closure 36 Model.

Author

Ahmadinia, Masoud, Sadri, Mahdi, Nobakht, Behzad, and Shariatipour, Seyed M.

Abstract

The UK plans to bring all greenhouse gas emissions to net-zero by 2050. Carbon capture and storage (CCS), an important strategy to reduce global CO2 emissions, is one of the critical objectives of this UK net-zero plan. Among the possible storage site options, saline aquifers are one of the most promising candidates for long-term CO2 sequestrations. Despite its promising potential, few studies have been conducted on the CO2 storage process in the Bunter Closure 36 model located off the eastern shore of the UK. Located amid a number of oil fields, Bunter is one of the primary candidates for CO2 storage in the UK, with plans to store more than 280 Mt of CO2 from injections starting in 2027. As saline aquifers are usually sparsely drilled with minimal dynamic data, any model is subject to a level of uncertainty. This is the first study on the impact of the model and fluid uncertainties on the CO2 storage process in Bunter. This study attempted to fully accommodate the uncertainty space on Bunter by performing twenty thousand forward simulations using a vertical equilibrium-based simulator. The joint impact of five uncertain parameters using data-driven models was analysed. The results of this work will improve our understanding of the carbon storage process in the Bunter model before the injection phase is initiated. Due to the complexity of the model, it is not recommended to make a general statement about the influence of a single variable on CO2 plume migration in the Bunter model. The reservoir temperature was shown to have the most impact on the plume dynamics (overall importance of 41%), followed by pressure (21%), permeability (17%), elevation (13%), and porosity (8%), respectively. The results also showed that a lower temperature and higher pressure in the Bunter reservoir condition would result in a higher density and, consequently, a higher structural capacity. [ABSTRACT FROM AUTHOR]

Published
2023
Full Text
View/download PDF

14. EFFECTS OF FLOW MEASUREMENT ERRORS ON OIL AND GAS PRODUCTION FORECASTS

Author

Shariatipour, Seyed and Sadri, Mahdi

Abstract

Different flow meter technologies are used to monitor the output of oil and gas wells. Although flowmeter accuracy has generally improved over time, there remain substantial uncertainties, particularly in multiphase flow. These errors could potentially be greater where older meters are being used for calibration, and/or maintenance is difficult. Consequently, the associated errors with the recorded data could be out of specification in such cases. One use of the well flow data is to improve parameter estimates for important characteristics of reservoirs such as porosity and permeability. Therefore, any errors in flow measurement influence the results of a reservoir simulation and production forecasts. However, the impact of flow measurement errors on the forecast of oil and gas production has not been considered before. In this study, the effects of using out-of-specification errors on the predicted reservoir production have been investigated. As a test case, the simulated production results of a reservoir with known characteristics were considered to be the actual flow rate values. Then, two sets of data were generated by applying errors up to 5% and 10%, respectively, to the flow rates and the resulting values were used in a history matching exercise to modify the predictions of the simulations for the same reservoir with incorrect porosity and permeability parameters. The errors in the first and second sets of data were considered to be within and without the specification, respectively. The results show that when errors are within the specification, the corrected porosity and permeability values have less than a 2.2% and 2.5% error, which cause minor deviations of up to 2.3% in the production forecast. However, for the second set of data, when the errors are increased up to 5% more than the specification, the corrected porosity, permeability and production forecast deviate significantly up to 10.8 %, 10.1% and 12.4% from their respective reference values.

Published
2018
Full Text
View/download PDF

17. Mitigating Allocation and Hydrocarbon Accounting Uncertainty Using More Frequent Flow Test Data

Author

Sadri, Mahdi and Shariatipour, Seyed M.

Abstract

Although the application of multi-phase flow meters has recently increased, the production of individual wells in many fields is still monitored by occasional flow tests using test separators. In the absence of flow measurement data during the time interval between two consecutive flow tests, the flow rates of wells are typically estimated using allocation techniques. As the flow rates, however, do not remain the same over the time between the tests, there is typically a large uncertainty associated with the allocated values. In this research, the effect of the frequency of flow tests on the estimated total production of wells, allocation, and hydrocarbon accounting has been investigated. Allocation calculations have been undertaken for three different cases using actual and simulated production data based on one to four flow tests per month. Allocation errors for each case have subsequently been obtained. The results show that for all the investigated cases, the average allocation error decreased when the number of flow tests per month increased. The sharpest error reduction has been observed when the frequency of the tests increased from one to two times per month. It reduced the allocation error for the three investigated cases by 0.43%, 0.45%, and 1.11% which are equivalent to $18.2M (million), $18.9M, and $46.8M reduction in the yearly cost of the allocation error for the respective cases. The reductions in the allocation error cost for the three cases were $27M, $29M, and $80M, respectively, when the flow tests have been undertaken weekly instead of monthly.

Published
2020
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results