Use Of Real-Time Surveillance Data For Reservoir Management In A Heterogeneous Carbonate Reservoir

2012 ◽  
Author(s):  
Lakshi Singha Konwar ◽  
Noura Al-Zaabi ◽  
Assif Mirza ◽  
Rakkad Al-Ameri ◽  
Syed M. Tariq
Keyword(s):  
Real Time ◽  
Reservoir Management ◽  
Carbonate Reservoir ◽  
Surveillance Data

Reservoir Management With Real-Time and Periodic Surveillance Data

2010 ◽  
Author(s):  
C. Shah Kabir ◽  
Danu Ismadi ◽  
Sandra R. Fountain
Keyword(s):  
Real Time ◽  
Reservoir Management ◽  
Surveillance Data

Malaria elimination in India requires additional surveillance mechanisms

2021 ◽  
Author(s):  
Manju Rahi ◽  
Payal Das ◽  
Amit Sharma
Keyword(s):  
Real Time ◽  
Malaria Elimination ◽  
Surveillance Data ◽  
Surveillance Systems ◽  
Malaria Surveillance ◽  
Aggregated Data ◽  
Malaria Burden ◽  
The Core ◽  
Reporting Systems ◽  
Geographic Regions

Abstract Malaria surveillance is weak in high malaria burden countries. Surveillance is considered as one of the core interventions for malaria elimination. Impressive reductions in malaria-associated morbidity and mortality have been achieved across the globe, but sustained efforts need to be bolstered up to achieve malaria elimination in endemic countries like India. Poor surveillance data become a hindrance in assessing the progress achieved towards malaria elimination and in channelizing focused interventions to the hotspots. A major obstacle in strengthening India’s reporting systems is that the surveillance data are captured in a fragmented manner by multiple players, in silos, and is distributed across geographic regions. In addition, the data are not reported in near real-time. Furthermore, multiplicity of malaria data resources limits interoperability between them. Here, we deliberate on the acute need of updating India’s surveillance systems from the use of aggregated data to near real-time case-based surveillance. This will help in identifying the drivers of malaria transmission in any locale and therefore will facilitate formulation of appropriate interventional responses rapidly.

Advances in Reservoir Management and Surveillance for a Giant Carbonate Reservoir

2015 ◽  
Author(s):  
M. A. Al-Marzouqi ◽  
J. D. Owens ◽  
A. Tee ◽  
S. A. Khan ◽  
S. S. Al-Muhairi ◽  
...  
Keyword(s):  
Reservoir Management ◽  
Carbonate Reservoir

Digital Workflow to Enhance Reservoir Management Strategies for A Complex Oil Field Through Real Time and Advanced Engineering Monitoring Solution

2021 ◽  
Author(s):  
Julieta Alvarez ◽  
Oswaldo Espinola ◽  
Luis Rodrigo Diaz ◽  
Lilith Cruces
Keyword(s):  
Real Time ◽  
Reservoir Characterization ◽  
Management Strategies ◽  
Reservoir Management ◽  
Gas Production ◽  
Oil Field ◽  
Oil Reservoirs ◽  
Production Operation ◽  
Digital Workflow ◽  
Operational Decisions

Abstract Increase recovery from mature oil reservoirs requires the definition of enhanced reservoir management strategies, involving the implementation of advanced methodologies and technologies in the field's operation. This paper presents a digital workflow enabling the integration of commonly isolated elements such as: gauges, flowmeters, inflow control devices; analysis methods and data, used to improve scientific understanding of subsurface flow dynamics and determine improved operational decisions that support field's reservoir management strategy. It also supports evaluation of reservoir extent, hydraulic communication, artificial lift impact in the near-wellbore zone and reservoir response to injected fluids and coning phenomenon. This latest is used as an example to demonstrate the applicability of this workflow to improve and support operational decisions, minimizing water and gas production due to coning, that usually results in increasing production operation costs and it has a direct impact decreasing reservoir energy in mature saturated oil reservoirs. This innovative workflow consists on the continuous interpretation of data from downhole gauges, referred in this paper as data-driven; as well as analytical and numerical simulation methodologies using real-time raw data as an input, referred in this paper as model-driven, not commonly used to analyze near wellbore subsurface phenomena like coning and its impact in surface operation. The resulting analyses are displayed through an extensive visualization tool that provides instant insight to reservoir characterization and productivity groups, improving well and reservoir performance prediction capabilities for complex reservoirs such as mature saturated reservoirs with an associated aquifer, where undesired water and gas production is a continuous challenge that incorporates unexpected operational expenses.

scholarly journals Accounting for healthcare-seeking behaviours and testing practices in real-time influenza forecasts

2018 ◽  
Author(s):  
Robert Moss ◽  
Alexander E Zarebski ◽  
Sandra J Carlson ◽  
James M McCaw
Keyword(s):  
Real Time ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Surveillance Data ◽  
Surveillance Systems ◽  
Healthcare Seeking ◽  
Public Health Decision ◽  
Predictive Skill ◽  
Health Decision ◽  
Substantial Change

AbstractFor diseases such as influenza, where the majority of infected persons experience mild (if any) symptoms, surveillance systems are sensitive to changes in healthcare-seeking and clinical decision-making behaviours. This presents a challenge when trying to interpret surveillance data in near-real-time (e.g., in order to provide public health decision-support). Australia experienced a particularly large and severe influenza season in 2017, perhaps in part due to (a) mild cases being more likely to seek healthcare; and (b) clinicians being more likely to collect specimens for RT-PCR influenza tests. In this study we used weekly Flutracking surveillance data to estimate the probability that a person with influenza-like illness (ILI) would seek healthcare and have a specimen collected. We then used this estimated probability to calibrate near-real-time seasonal influenza forecasts at each week of the 2017 season, to see whether predictive skill could be improved. While the number of self-reported influenza tests in the weekly surveys are typically very low, we were able to detect a substantial change in healthcare seeking behaviour and clinician testing behaviour prior to the high epidemic peak. Adjusting for these changes in behaviour in the forecasting framework improved predictive skill. Our analysis demonstrates a unique value of community-level surveillance systems, such as Flutracking, when interpreting traditional surveillance data.

Utilizing NMR Workflow to Optimize Power Water Injector Placement in the Presence of Tar Barriers

2021 ◽  
Author(s):  
Gabor Hursan ◽  
Mohammed Sahhaf ◽  
Wala’a Amairi
Keyword(s):  
Spectral Analysis ◽  
Pore Size ◽  
Real Time ◽  
Total Porosity ◽  
Carbonate Reservoir ◽  
Wettability Alteration ◽  
Well Placement ◽  
Carbonate Formation ◽  
Fluid Saturation ◽  
Rock Quality

Abstract The objective of this work is to optimize the placement of horizontal power water injector (PWI) wells in stratified heterogeneous carbonate reservoir with tar barriers. The key to successful reservoir navigation is a reliable real-time petrophysical analysis that resolves rock quality variations and differentiates tar barriers from lighter hydrocarbon intervals. An integrated workflow has been generated based on logging-while drilling (LWD) triple combo and Nuclear Magnetic Resonance (NMR) logging data for fluid identification, tar characterization and permeability prediction. The workflow has three steps; it starts with the determination of total porosity using density and neutron logs, the calculation of water-filled porosity from resistivity measurements and an additional partitioning of porosity into bound and free fluid volumes using the NMR data. Second, the total and water-filled porosity, the NMR bound fluid and NMR total porosity are used as inputs in a hydrocarbon compositional and viscosity analysis of hydrocarbon-bearing zones for the recognition of tar-bearing and lighter hydrocarbon intervals. Third, in the lighter hydrocarbon intervals, NMR logs are further analyzed using a multi-cutoff spectral analysis to identify microporous and macroporous zones and to calculate the NMR mobility index. The ideal geosteering targets are highly macroporous rocks containing no heavy hydrocarbons. In horizontal wells, the method is validated using formation pressure while drilling (FPWD) measurements. The procedure has been utilized in several wells. The original well path of the first injector was planned to maintain a safe distance above an anticipated tar-bearing zone. Utilizing the new real-time viscosity evaluation, the well was steered closer to the tar zone several feet below the original plan, setting an improved well placement protocol for subsequent injectors. In the water- or lighter hydrocarbon-bearing zones, spectral analysis of NMR logs clearly accentuated micro- and macroporous carbonate intervals. The correlation between pore size and rock quality has been corroborated by FPWD mobility measurements. In one well, an extremely slow NMR relaxation may indicate wettability alteration in a macroporous interval. An integrated real-time evaluation of porosity, fluid saturation, hydrocarbon viscosity and pore size has enhanced well placement in a heterogeneous carbonate formation where tar barriers are also present. The approach increased well performance and substantially improved reservoir understanding.

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