scholarly journals Tight Reservoir Properties Derived by Nuclear Magnetic Resonance, Mercury Porosimetry and Computed Microtomography Laboratory Techniques. Case Study of Palaeozoic Clastic Rocks

2015 ◽  
Vol 63 (3) ◽  
pp. 789-814 ◽  
Author(s):  
Paulina I. Krakowska ◽  
Edyta Puskarczyk
Keyword(s):  
Nuclear Magnetic Resonance ◽  
Magnetic Resonance ◽  
Mercury Porosimetry ◽  
Reservoir Properties ◽  
Clastic Rocks ◽  
Laboratory Techniques ◽  
Tight Reservoir ◽  
Computed Microtomography ◽  
Nuclear Magnetic

Static Measurements Enhance Saturation and Permeability Interpretation

2021 ◽  
Vol 73 (08) ◽  
pp. 46-47
Author(s):  
Chris Carpenter
Keyword(s):  
Nuclear Magnetic Resonance ◽  
Magnetic Resonance ◽  
Water Saturation ◽  
Data Gathering ◽  
Abu Dhabi ◽  
Rock Properties ◽  
Well Test ◽  
Reservoir Properties ◽  
Nuclear Magnetic

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 202683, “Marrying the Static and Dynamic Worlds: Enhancing Saturation and Permeability Interpretation Using a Combination of Multifrequency Dielectric, Nuclear Magnetic Resonance, and Wireline Formation Testers,” by Hassan Mostafa, Ghassan Al-Jefri, SPE, and Tania Felix Menchaca, SPE, ADNOC, et al., prepared for the 2020 Abu Dhabi International Petroleum Exhibition and Conference, Abu Dhabi, held virtually 9–12 November. The paper has not been peer reviewed. Accurate water saturation evaluation and permeability profiling are crucial factors in determining volumetrics and productivity of multiple, stacked carbonate reservoirs offshore Abu Dhabi and derisking reservoir management. The case study presented in the complete paper illustrates how the integration of static measurements, such as dielectric dispersion and nuclear magnetic resonance (NMR) with dynamic measurements improves understanding of reservoir properties and supports more-accurate reservoir evaluation. Sampling and downhole fluid analysis (DFA) performed by wireline formation tester (WFT) identifies the fluid and rock properties in various flow units. Field Background and Challenges Optimal field development requires accurate estimations of water saturation and permeability. In this greenfield, the hydrocarbon is generally oil (medium to light) with very low asphaltene content. Overall, the reservoir quality is controlled by a combination of depositional environment, sequence stratigraphy, and diagenesis. Some reservoirs have good porosity, but reconciliation of log-based water saturation results with well-test results has been an issue. The objective in this case study was to drill a pilot hole for data gathering in a poorly characterized field location. Phase I included drilling a hole with a 55° deviation to cover all reservoirs for data gathering only, with the openhole reservoir section then being plugged and abandoned. Phase II of the plan was to sidetrack and complete the well as dual water-injector boreholes. In the reservoir section of the pilot borehole, a variety of logs was acquired for evaluation, including both logging-while-drilling and wireline measurements. While drilling, triple- combination data were acquired, consisting of gamma ray, resistivity, and nuclear logs (density neutron) along with resistivity images. The wireline-logging program was carried out in two stages to avoid differential sticking. In the first stage, the WFT was used to acquire 10 pressure points, seven points in the first reservoir and three points in the second. Two DFA stations were also recorded in Zone 1 to confirm whether the oil/water contact was deeper than expected. Logging was conducted using a high-tension wireline cable, which facilitates quicker accessibility to the openhole sections. In the second stage, multiple wireline runs were performed for the formation evaluation of the complete section, followed by the WFT pressure and fluid-sampling run on the drillpipe conveyance. Another critical challenge was to obtain accurate water saturations in the heterogeneous, minor, thin reservoirs, which are bounded by dense layers above and below and cause shoulder-bed effects. The third challenge in this well was to obtain an accurate, continuous, and representative permeability profile for the multiple reservoirs. WFT mini-drillstem test (DST) stations along with NMR logs were used to address this important requirement.

scholarly journals Differences in metabolic profiles of planktonic and biofilm cells in Staphylococcus aureus - (1)H Nuclear Magnetic Resonance search for candidate biomarkers.

1970 ◽  
Vol 60 (4) ◽  
Author(s):  
Adam Feliks Junka ◽  
Stanisław Deja ◽  
Danuta Smutnicka ◽  
Patrycja Szymczyk ◽  
Grzegorz Ziółkowski ◽  
...  
Keyword(s):  
Staphylococcus Aureus ◽  
Nuclear Magnetic Resonance ◽  
Magnetic Resonance ◽  
Principal Component ◽  
Clinical Diagnostics ◽  
Future Application ◽  
Computed Microtomography ◽  
Resonance Search ◽  
X Ray Computed ◽  
Nuclear Magnetic

Staphylococcus aureus is responsible for many types of infections related to biofilm presence. As the early diagnostics remains the best option for prevention of biofilm infections, the aim of the work presented was to search for differences in metabolite patterns of S. aureus ATCC6538 biofilm vs. free-swimming S. aureus planktonic forms. For this purpose, Nuclear Magnetic Resonance (NMR) spectroscopy was applied. Data obtained were supported by means of Scanning Electron Microscopy, quantitative cultures and X-ray computed microtomography. Metabolic trends accompanying S. aureus biofilm formation were found using Principal Component Analysis (PCA). Levels of isoleucine, alanine and 2,3-butanediol were significantly higher in biofilm than in planktonic forms, whereas level of osmoprotectant glycine-betaine was significantly higher in planktonic forms of S. aureus. Results obtained may find future application in clinical diagnostics of S. aureus biofilm-related infections.

scholarly journals Synthesizing Nuclear Magnetic Resonance (NMR) Outputs for Clastic Rocks Using Machine Learning Methods, Examples from North West Shelf and Perth Basin, Western Australia

Energies ◽  
2022 ◽  
Vol 15 (2) ◽  
pp. 518
Author(s):  
Reza Rezaee
Keyword(s):  
Machine Learning ◽  
Nuclear Magnetic Resonance ◽  
Relaxation Time ◽  
Magnetic Resonance ◽  
Western Australia ◽  
Well Logs ◽  
T2 Relaxation Time ◽  
T2 Relaxation ◽  
Clastic Rocks ◽  
Nuclear Magnetic

A nuclear magnetic resonance (NMR) logging tool can provide important rock and fluid properties that are necessary for a reliable reservoir evaluation. Pore size distribution based on T2 relaxation time and resulting permeability are among those parameters that cannot be provided by conventional logging tools. For wells drilled before the 1990s and for many recent wells there is no NMR data available due to the tool availability and the logging cost, respectively. This study used a large database of combinable magnetic resonance (CMR) to assess the performance of several well-known machine learning (ML) methods to generate some of the NMR tool’s outputs for clastic rocks using typical well-logs as inputs. NMR tool’s outputs, such as clay bound water (CBW), irreducible pore fluid (known as bulk volume irreducible, BVI), producible fluid (known as the free fluid index, FFI), logarithmic mean of T2 relaxation time (T2LM), irreducible water saturation (Swirr), and permeability from Coates and SDR models were generated in this study. The well logs were collected from 14 wells of Western Australia (WA) within 3 offshore basins. About 80% of the data points were used for training and validation purposes and 20% of the whole data was kept as a blind set with no involvement in the training process to check the validity of the ML methods. The comparison of results shows that the Adaptive Boosting, known as AdaBoost model, has given the most impressive performance to predict CBW, FFI, permeability, T2LM, and SWirr for the blind set with R2 more than 0.9. The accuracy of the ML model for the blind dataset suggests that the approach can be used to generate NMR tool outputs with high accuracy.

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