Robust Screening Criteria for Foam-Assisted Water-Alternating Gas FAWAG Injection

2021 ◽  
Author(s):  
Nor Idah Kechut ◽  
Johannes A.W.M Groot ◽  
Mohd Azlan Mustafa ◽  
Jeroen Groenenboom

Abstract Foam-Assisted-Water-Alternating-Gas (FAWAG) injection has been proposed to improve the inherent unfavorable mobility ratio of gas and liquid in WAG process. The foam reduces gravity override and gas channeling as to improve volumetric sweep efficiency and thus oil recovery. There are still a lot of uncertainties yet to be understood in foam dynamics, surfactant adsorption, and foam stability when contacting oil, which impact the actual foam propagation into the reservoir. Although some insights are gained from laboratory and field experiments, the performance, and design of the injection strategy and facilities as part of the field development of FAWAG is not trivial and field data is sparse. Extensive laboratory experiments and simulation studies are necessary to de-risk enhanced oil recovery (EOR) application, but these processes are time consuming and expensive. For this reason, a screening study is normally conducted to increase the possibility of selecting high potential candidates prior to embarking on the detailed feasibility studies. Unfortunately for FAWAG, the screening criteria are not readily established nor commonly available in commercial screening tools unlike for other matured EOR methods, largely contributed by the limited database on FAWAG field implementations worldwide. This paper presents a robust FAWAG screening tool which accounts for important reservoir properties, uncertainties in foam model parameters, as well as various reservoir conditions of oil and gas production and injection plans. The FAWAG process is modelled from the assumption of local equilibrium of foam creation and coalescence using an Implicit Texture model. Relevant foam scan experiments/steady state coreflood data were analyzed to derive parameters that characterize foam dynamics. The sensitivity study in this paper ranks and identifies the main risks and opportunities for the FAWAG process, quantifies the reliability of the model and increases the understanding of the effective dynamic behaviour. The sensitivity study was the basis for the development and validation of a proxy model by design of experiments. The screening tool employs this proxy model to generate immediate screening results without the need to run additional simulations. The screening tool was further validated with upscaled experimental data. A set of prediction results on the range of oil recovery for numerous plausible field scenarios was established; these screening criteria will be used as the basis for high-level decision making.

2017 ◽  
Vol 1 (2) ◽  
pp. 54 ◽  
Author(s):  
Soheil Bahrekazemi ◽  
Mahnaz Hekmatzadeh

Assessment of the suitable enhanced oil recovery method in an oilfield is one of the decisions which are made prior to the natural drive production mechanism. In some cases, having in-depth knowledge about reservoir’s rock, fluid properties, and equipment is needed as well as economic evaluation. Both putting such data into simulation and its related consequent processes are generally very time consuming and costly.  In order to reduce study cases, an appropriate tool is required for primary screening prior to any operations being performed, to which leads reduction of time in design of ether pilot section or production under field condition. In this research, two different and useful screening tools are presented through a graphical user interface. The output of just over 900 simulations and verified screening criteria tables were employed to design the mentioned tools. Moreover, by means of gathered data and development of artificial neural networks, two dissimilar screening tools for proper assessment of suitable enhanced oil recovery method were finally introduced. The first tool is about the screening of enhanced oil recovery process based on published tables/charts and the second one which is Neuro-Simulation tool, concerns economical evaluation of miscible and immiscible injection of carbon dioxide, nitrogen and natural gas into the reservoir. Both of designed tools are provided in the form of a graphical user interface by which the user, can perceive suitable method through plot of oil recovery graph during 20 years of production, costs of gas injection per produced barrel, cumulative oil production, and finally, design the most efficient scenario.


Author(s):  
Azza Hashim Abbas ◽  
Hani Hago Elhag ◽  
Wan Rosli Wan Sulaiman ◽  
Afeez Gbadamosi ◽  
Peyman Pourafshary ◽  
...  

AbstractEnhanced oil recovery (EOR) is a proven method to increase oil production from the brown fields. One of the efficient EOR methods is injecting surfactants to release the trapped oil. However, few unconsolidated behaviours were observed in both field and laboratory practice. In this study, a new framework was adapted to evaluate the continuous surfactant flooding (CSF) in Bentiu reservoir. The study aims to quantify the expected range of the oil production, recovery factor and residual oil saturation (Sor). The motivation came from the oil demand in Sudan and the insufficient cores. The framework adopted in the study includes numerical simulation modelling and proxy modelling. Thirty-six cores obtained from the field were revised and grouped into five main groups. The interfacial tension (IFT) data were obtained experimentally. The CSF sensitivity study was developed by combining different experimental design sets to generate the proxy model. The CSF numerical simulation results showed around 30% additional oil recovery compared to waterflooding and approximately oil production between (20–30) cm3. The generated proxy model extrapolated the results with concerning lower ranges of the input and showed an average P50 of oil production and recovery of 74% and 17 cm3, respectively. Overall, the performance of CSF remained beneficial in vast range of input. Moreover, the generated proxy model gave an insight on the complexity of the interrelationship between the input factors and the observants with a qualitative prospective factors. Yet, the results confirmed the applicability of CSF in core scale with an insight for field scale application.


2021 ◽  
Vol 2 (1) ◽  
pp. 1
Author(s):  
Mohammed Samba ◽  
Yiqiang Li ◽  
Madi Abdullah Naser ◽  
Mahmoud O Elsharafi

There are many known enhanced oil recovery (EOR) methods and every method has its criteria to use it. Some of those methods are gas injection such as CO2 injection, N2 and hydrocarbon gas injection. Where the CO2 has been the largest contributor to global EOR. Gas injection can be classified into two main types; continues gas injection (CGI) and water alternating gas injection (WAG). The objective of this research is to propose initial gases injection plan of the X field to maximize the total oil recovery. The feasibility study of different gases to maintain pressure and optimize oil recovery have been examined on a simple mechanistic reservoir model of considerably depleted saturated oil reservoir. In order to maximize the total oil recovery, the simulation study was conducted on 3-phase compositional simulation model. For more optimization, a sensitivity study was conducted on the injection cycling and component ratios. A sensitivity study was also conducted on the following parameters to study their effects on the overall field’s recovery such as flow rate and bottom-hole pressure. Results obtained in this paper shows that, the WAG CO2 injection was found to be significantly more efficient than different gas injection and continues gas injection. The oil recovery depends not only on the fluid-to-fluid displacement but also on the compositional phase behavior. 


Water ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 463
Author(s):  
Gopinathan R. Abhijith ◽  
Leonid Kadinski ◽  
Avi Ostfeld

The formation of bacterial regrowth and disinfection by-products is ubiquitous in chlorinated water distribution systems (WDSs) operated with organic loads. A generic, easy-to-use mechanistic model describing the fundamental processes governing the interrelationship between chlorine, total organic carbon (TOC), and bacteria to analyze the spatiotemporal water quality variations in WDSs was developed using EPANET-MSX. The representation of multispecies reactions was simplified to minimize the interdependent model parameters. The physicochemical/biological processes that cannot be experimentally determined were neglected. The effects of source water characteristics and water residence time on controlling bacterial regrowth and Trihalomethane (THM) formation in two well-tested systems under chlorinated and non-chlorinated conditions were analyzed by applying the model. The results established that a 100% increase in the free chlorine concentration and a 50% reduction in the TOC at the source effectuated a 5.87 log scale decrement in the bacteriological activity at the expense of a 60% increase in THM formation. The sensitivity study showed the impact of the operating conditions and the network characteristics in determining parameter sensitivities to model outputs. The maximum specific growth rate constant for bulk phase bacteria was found to be the most sensitive parameter to the predicted bacterial regrowth.


CNS Spectrums ◽  
2021 ◽  
Vol 26 (2) ◽  
pp. 181-183
Author(s):  
Michael E. Thase ◽  
Stephen M. Stahl ◽  
Roger S. McIntyre ◽  
Tina Matthews-Hayes ◽  
Mehul Patel ◽  
...  

AbstractIntroductionAlthough mania is the hallmark symptom of bipolar I disorder (BD-I), most patients initially present for treatment with depressive symptoms. Misdiagnosis of BD-I as major depressive disorder (MDD) is common, potentially resulting in poor outcomes and inappropriate antidepressant monotherapy treatment. Screening patients with depressive symptoms is a practical strategy to help healthcare providers (HCPs) identify when additional assessment for BD-I is warranted. The new 6-item Rapid Mood Screener (RMS) is a pragmatic patient-reported BD-I screening tool that relies on easily understood terminology to screen for manic symptoms and other BD-I features in <2 minutes. The RMS was validated in an observational study in patients with clinically confirmed BD-I (n=67) or MDD (n=72). When 4 or more items were endorsed (“yes”), the sensitivity of the RMS for identifying patients with BP-I was 0.88 and specificity was 0.80; positive and negative predictive values were 0.80 and 0.88, respectively. To more thoroughly understand screening tool use among HCPs, a 10-minute survey was conducted.MethodsA nationwide sample of HCPs (N=200) was selected using multiple HCP panels; HCPs were asked to describe their opinions/current use of screening tools, assess the RMS, and evaluate the RMS versus the widely recognized Mood Disorder Questionnaire (MDQ). Results were reported by grouped specialties (primary care physicians, general nurse practitioners [NPs]/physician assistants [PAs], psychiatrists, and psychiatric NPs/PAs). Included HCPs were in practice <30 years, spent at least 75% of their time in clinical practice, saw at least 10 patients with depression per month, and diagnosed MDD or BD in at least 1 patient per month. Findings were reported using descriptive statistics; statistical significance was reported at the 95% confidence interval.ResultsAmong HCPs, 82% used a tool to screen for MDD, while 32% used a tool for BD. Screening tool attributes considered to be of the greatest value included sensitivity (68%), easy to answer questions (66%), specificity (65%), confidence in results (64%), and practicality (62%). Of HCPs familiar with screening tools, 70% thought the RMS was at least somewhat better than other screening tools. Most HCPs were aware of the MDQ (85%), but only 29% reported current use. Most HCPs (81%) preferred the RMS to the MDQ, and the RMS significantly outperformed the MDQ across valued attributes; 76% reported that they were likely to use the RMS to screen new patients with depressive symptoms. A total of 84% said the RMS would have a positive impact on their practice, with 46% saying they would screen more patients for bipolar disorder.DiscussionThe RMS was viewed positively by HCPs who participated in a brief survey. A large percentage of respondents preferred the RMS over the MDQ and indicated that they would use it in their practice. Collectively, responses indicated that the RMS is likely to have a positive impact on screening behavior.FundingAbbVie Inc.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Nichtima Chayaopas ◽  
Pornthep Kasemsiri ◽  
Panida Thanawirattananit ◽  
Patorn Piromchai ◽  
Kwanchanok Yimtae

Abstract Background Globally increasing number of elders is concerned. Hearing loss process in older adults cannot be avoided. An effective screening tool for hearing loss is essential for proper diagnosis and rehabilitation, which can improve QOL in older adults. Methods This prospective-diagnostic test study evaluates the diagnostic value of Thai version of the Hearing Handicap Inventory for Elderly Screening (HHIE-ST) and the Thai Single Question (TSQ) surveys in screening hearing disability in 1109 Thai participants aged 60 years and older in communities in four provinces in Thailand. The HHIE-ST consisted of 10 selected questions from the validated HHIE-Thai version. A TSQ survey was developed to have the same meaning as an English Single Question survey. The participants answered both questionnaires, and a standard audiometry test assessed with air conduction from 250 to 8000 Hz was included as a gold standard. Results The prevalence of hearing disability was 38.34%. The HHIE-ST achieved a sensitivity of 88.96% (95% CI 85.77–91.64) and specificity of 52.19% (95% CI 48.24–56.13) for diagnosis hearing disability in Thai older adults, whereas the TSQ yielded a sensitivity of 88.73% and a specificity of 55.93%. A combined test including the HHIE-ST and TSQ achieved better performance with sensitivity of 85.29% and specificity of 60.13%. Conclusions Either the HHIE-ST or the TSQ is a sensitive and useful tool for screening hearing disability in Thai older adults. Using the HHIE-ST together with the TSQ resulted in a better screening tool for detecting moderate hearing loss older adults who will benefit and recommended for hearing rehabilitation. Trial registration The study is registered with the following number in the Thai Clinical Trials Registry: TCTR20151015003. Date of registration October 14, 2015.


2011 ◽  
Author(s):  
Abdulrazag Yusef Zekri ◽  
Mohamed Sanousi Nasr ◽  
Abdullah AlShobakyh

Diagnostics ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 905
Author(s):  
Ahmed Elwali ◽  
Zahra Moussavi

Background: The apnea/hypopnea index (AHI) is the primary outcome of a polysomnography assessment (PSG) for determining obstructive sleep apnea (OSA) severity. However, other OSA severity parameters (i.e., total arousal index, mean oxygen saturation (SpO2%), etc.) are crucial for a full diagnosis of OSA and deciding on a treatment option. PSG assessments and home sleep tests measure these parameters, but there is no screening tool to estimate or predict the OSA severity parameters other than the AHI. In this study, we investigated whether a combination of breathing sounds recorded during wakefulness and anthropometric features could be predictive of PSG parameters. Methods: Anthropometric information and five tracheal breathing sound cycles were recorded during wakefulness from 145 individuals referred to an overnight PSG study. The dataset was divided into training, validation, and blind testing datasets. Spectral and bispectral features of the sounds were evaluated to run correlation and classification analyses with the PSG parameters collected from the PSG sleep reports. Results: Many sound and anthropometric features had significant correlations (up to 0.56) with PSG parameters. Using combinations of sound and anthropometric features in a bilinear model for each PSG parameter resulted in correlation coefficients up to 0.84. Using the evaluated models for classification with a two-class random-forest classifier resulted in a blind testing classification accuracy up to 88.8% for predicting the key PSG parameters such as arousal index. Conclusions: These results add new value to the current OSA screening tools and provide a new promising possibility for predicting PSG parameters using only a few seconds of breathing sounds recorded during wakefulness without conducting an overnight PSG study.


2021 ◽  
pp. 1-18
Author(s):  
Gisela Vanegas ◽  
John Nejedlik ◽  
Pascale Neff ◽  
Torsten Clemens

Summary Forecasting production from hydrocarbon fields is challenging because of the large number of uncertain model parameters and the multitude of observed data that are measured. The large number of model parameters leads to uncertainty in the production forecast from hydrocarbon fields. Changing operating conditions [e.g., implementation of improved oil recovery or enhanced oil recovery (EOR)] results in model parameters becoming sensitive in the forecast that were not sensitive during the production history. Hence, simulation approaches need to be able to address uncertainty in model parameters as well as conditioning numerical models to a multitude of different observed data. Sampling from distributions of various geological and dynamic parameters allows for the generation of an ensemble of numerical models that could be falsified using principal-component analysis (PCA) for different observed data. If the numerical models are not falsified, machine-learning (ML) approaches can be used to generate a large set of parameter combinations that can be conditioned to the different observed data. The data conditioning is followed by a final step ensuring that parameter interactions are covered. The methodology was applied to a sandstone oil reservoir with more than 70 years of production history containing dozens of wells. The resulting ensemble of numerical models is conditioned to all observed data. Furthermore, the resulting posterior-model parameter distributions are only modified from the prior-model parameter distributions if the observed data are informative for the model parameters. Hence, changes in operating conditions can be forecast under uncertainty, which is essential if nonsensitive parameters in the history are sensitive in the forecast.


2021 ◽  
Author(s):  
Thaer I. Ismail ◽  
Emad W. Al-Shalabi ◽  
Mahmoud Bedewi ◽  
Waleed AlAmeri

Abstract Gas injection is one of the most commonly used enhanced oil recovery (EOR) methods. However, there are multiple problems associated with gas injection including gravity override, viscous fingering, and channeling. These problems are due to an adverse mobility ratio and cause early breakthrough of the gas resulting, in poor recovery efficiency. A Water Alternating Gas (WAG) injection process is recommended to resolve these problems through better mobility control of gas, leading to better project economics. However, poor WAG design and lack of understanding of the different factors that control its performance might result in unfavorable oil recovery. Therefore, this study provides more insight into improving WAG oil recovery by optimizing different surface and subsurface WAG parameters using a coupled surface and subsurface simulator. Moreover, the work investigates the effects of hysteresis on WAG performance. This case study investigates a field named Volve, which is a decommissioned sandstone field in the North Sea. Experimental design of factors influencing WAG performance on this base case was studied. Sensitivity analysis was performed on different surface and subsurface WAG parameters including WAG ratio, time to start WAG, total gas slug size, cycle slug size, and tubing diameter. A full two-level factorial design was used for the sensitivity study. The significant parameters of interest were further optimized numerically to maximize oil recovery. The results showed that the total slug size is the most important parameter, followed by time to start WAG, and then cycle slug size. WAG ratio appeared in some of the interaction terms while tubing diameter effect was found to be negligible. The study also showed that phase hysteresis has little to no effect on oil recovery. Based on the optimization, it is recommended to perform waterflooding followed by tertiary WAG injection for maximizing oil recovery from the Volve field. Furthermore, miscible WAG injection resulted in an incremental oil recovery between 5 to 11% OOIP compared to conventional waterflooding. WAG optimization is case-dependent and hence, the findings of this study hold only for the studied case, but the workflow should be applicable to any reservoir. Unlike most previous work, this study investigates WAG optimization considering both surface and subsurface parameters using a coupled model.


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