Relevant bibliographies by topics / Well log interpretation

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  2. Dissertations / Theses
  3. Books
  4. Book chapters
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Academic literature on the topic 'Well log interpretation'

Author: Grafiati
Published: 4 June 2021
Last updated: 28 January 2023

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Journal articles on the topic "Well log interpretation"

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King, D. E. "Incorporating geological data in well log interpretation." Geological Society, London, Special Publications 48, no. 1 (1990): 45–55. http://dx.doi.org/10.1144/gsl.sp.1990.048.01.06.

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Wu, Xuanzhi, and Edo Nyland. "Automated stratigraphic interpretation of well‐log data." GEOPHYSICS 52, no. 12 (December 1987): 1665–76. http://dx.doi.org/10.1190/1.1442283.

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A computerized well‐log stratigraphic interpretation system based on artificial intelligence can be seen as two steps, contact recognition and interval identification. Unlike previous approaches to mathematical zonation which are essentially statistical, consideration of the geologic environment is included for effective interpretation. Following the logic of human experts, the system first determines the log signature of the contacts. An algorithm incorporating linear regression with variable breakpoints is used to describe the structure of log curves. Log features are mapped to the assigned signature of contacts. Multiple logs are taken into account to set up the final set of contacts, which divides the test borehole into a string of intervals with attributes. A pattern string of intervals is based on the integrated geologic column for the section where the borehole is located. A string‐to‐string matching program then determines the optimal map of the test borehole as the pattern to generate a geologic column based on the computer suggestion. The cost formulas for matching represent knowledge about the stratigraphy of the area under study, and the string‐to‐string matching algorithm includes this knowledge of stratigraphy. In test boreholes in an oil‐sand deposit, 86 percent of the computer identifications of intervals were consistent with those determined by geologists from core descriptions, suggesting that the design concept and computer algorithm are consistent with the characteristics of the interpretation problem.
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Buoro, Alvaro Bueno, and João B. C. Silva. "Ambiguity analysis of well‐log data." GEOPHYSICS 59, no. 3 (March 1994): 336–44. http://dx.doi.org/10.1190/1.1443595.

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Ambiguity in a geophysical interpretation problem is the possibility of accepting more than one solution caused either by solution nonuniqueness or instability. Nonuniqueness is related to the existence of more than one solution regardless of the precision of observations. On the other hand, instability is related to the acceptance of different solutions producing data fittings within the expected observational errors. We studied the ambiguity in the inversion of well‐logging data using a method based on the analysis of a finite number of acceptable solutions, which are ordered, in the solution space, according to their contributions to the overall ambiguity. The analysis of the parameter variations along these ordered solutions provides an objective way to characterize the most ambiguous parameters. Because this analysis is based on the geometry of an ambiguity region, empirically estimated by a finite number of alternative solutions, it is possible to analyze the ambiguity due not only to errors in the observations, but also to discrepancies between the interpretation model and the true geology. Moreover, the analysis can be applied even in the case of a nonlinear interpretation model. The analysis was performed with recorded data, and compared with the analysis using singular value decomposition, leading to comparable results. Following the determination of the most ambiguous parameters, a reparameterization is possible by grouping these parameters into a single parameter leading to a simpler interpretation model and, therefore, to a drastic reduction in the ambiguity.
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Alcolea Rodríguez, Andrés, Paul Marschall, Christophe Nussbaum, and Jens Karl Becker. "Automatic interpretation of geophysical well logs." Geological Society, London, Special Publications 482, no. 1 (September 21, 2018): 25–38. http://dx.doi.org/10.1144/sp482.9.

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AbstractStratigraphic sequences in boreholes are commonly estimated by interpreting combinations of well logs. The interpretation is generally tedious and is made some time after log completion, which often leads to a loss of valuable first-hand information gathered on-site. This may lead to delayed or potentially poor on-site decisions. To make things worse, the standard interpretation of well logs is, at least to a certain degree, subjective and based on the manipulation of data, which may be difficult to trace in the long term. Small changes in lithology are often disregarded and alternating thin layers presenting different lithologies are often combined in one single (notably thicker) stratigraphic unit. Therefore an automatic parameter-based and thus traceable and objective quick look at the lithology immediately after log completion represents both a valuable tool to help with on-site decisions and a solid, mathematically based starting point for further physically based interpretations carried out by log analysts. We present a workflow for the interpretation of well logs defined as an optimization problem. The workflow is applied to the characterization of metre- to decametre-scale stratigraphic units along 13 boreholes in northern Switzerland (one-dimensional resolution) and to millimetre-scale features over a wall at the Mont Terri underground rock laboratory in Switzerland (two-dimensional resolution). The results show that: (1) the workflow accurately maps lithological changes; (2) the interaction with the analyst is minimized, which reduces the subjectivity of the interpretation; and (3) outputs are available for on-site decisions.
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Jahani, Nazanin, Joaquin Ambia Garrido, Sergey Alyaev, Kristian Fossum, Erich Suter, and Carlos Torres-Verdín. "Ensemble-based well-log interpretation and uncertainty quantification for well geosteering." GEOPHYSICS 87, no. 3 (April 11, 2022): IM57—IM66. http://dx.doi.org/10.1190/geo2021-0151.1.

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Hydrocarbon reservoirs are often located in spatially complex and uncertain geologic environments, where the associated costs of drilling wells for exploration and development are notoriously high. These costs may be reduced with an optimized well-placement strategy based on real-time geologic information, known as well geosteering. To effectively place the well in an updated geomodel and support well geosteering decisions in real time, we apply an iterative inversion approach based on the Levenberg-Marquardt form of the ensemble randomized maximum likelihood method. The method estimates geomodel properties together with their uncertainties by reducing the statistical misfit between the measurements acquired with well-logging tools and the predicted measurements from numerical simulations. Analyses of synthetic cases indicate that the method’s reliability and computational speed depend on the distance from the logging tool to formation boundaries, the contrast of model properties, and the thickness of formation layers. Our method delivers reliable estimates of model properties with only 40 ensemble members and 2–10 iterations; hence, it is approximately 10–125 times faster than Metropolis-Hastings Monte Carlo, which we use as a baseline condition given its proven track record. Likewise, our method is amenable to parallelization to further reduce computational times. Implementation of the method with a synthetic example inspired by a historical well geosteering operation yields accurate formation evaluation and verifies its accurate and reliable performance under complex geologic conditions.
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Spalburg, Mirano R. "A Fast and Transparent Bayesian Log Interpretation Method." Petrophysics – The SPWLA Journal of Formation Evaluation and Reservoir Description 63, no. 4 (August 1, 2022): 534–48. http://dx.doi.org/10.30632/pjv63n4-2022a4.

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This paper presents a fast and transparent Bayesian-based computational method that can be used for the interpretation of well logs. Rather than single values for formation properties, the results are probability distributions. The method is fast because the responses of logging tools, for a large set of formation realizations, are calculated only once and then stored with the realizations in a database. Thereafter, only this database is used for the interpretation of real well logs. The method is transparent because it entirely relies on selecting formation realizations with calculated log responses that are, within a given error margin, equal to the real logging tool responses. Therefore, only internally consistent interpretations can be found. The size of the database is realizable and the log evaluation computation time sufficiently short. The method has been tested with good results on more than 100 wells. Some of the well results are presented and discussed. The presented evaluations use databases of about 300 MB containing about 25 million realizations. Database construction and whole well evaluation each require less than a few seconds.
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Sari, Tri Wulan, and Sujito Sujito. "LITHOLOGY INTERPRETATION BASED ON WELL LOG DATA ANALYSIS IN “JS” FIELD." Applied Research on Civil Engineering and Environment (ARCEE) 1, no. 01 (October 28, 2019): 31–37. http://dx.doi.org/10.32722/arcee.v1i01.1955.

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Reservoir lithology types in a prospect zone of hydrocarbon can be known through well log data analysis, both qualitatively and quantitatively. Lithology interpretation based on qualitatively well log data analysis, has been successfully carried out by K-1 and K-3 well log data on JS Field, West Natuna basin, Riau Islands.Main focus of the research is types of lithology indicated by response the petrophysical well data log of Lower-Middle Miocene Arang Formation. Arang Formation was deposited immediately on top Barat formation and depositional environment in this formation is transitional marine - marine. Petrophysics log shows well data are log gamma ray, resistivity, neutron porosity, density, and sonic. The limitation of study are on four types lithology, they are coal, sand, sally sand, and shale. Lithology on well K-1 dominate by shale, there is thin intersection between sand and coal. The well of K-1 have sand thickest around six meter. While on well K-3 Petrophysics log data shows thin intersection between coal, sand, shaly sand, and dominated by shale. The thickest Sand have thickness 29 meter, and thicker than on K-1 well. The result in this study, the formation dominated by types of lithology “shale”.
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ASAKURA, NATSUO. "3D seismic interpretation integrated by VSP and well log data." Journal of the Japanese Association for Petroleum Technology 51, no. 1 (1986): 2–15. http://dx.doi.org/10.3720/japt.51.2.

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Szucs, Peter, and Faruk Civan. "Multi-layer well log interpretation using the simulated annealing method." Journal of Petroleum Science and Engineering 14, no. 3-4 (May 1996): 209–20. http://dx.doi.org/10.1016/0920-4105(95)00048-8.

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Ezeh, Sunny C., Wilfred A. Mode, Berti M. Ozumba, and Nura A. Yelwa. "Sedimentology and ichnology of Neogene Coastal Swamp deposits in the Niger Delta Basin, Nigeria." Geologos 22, no. 3 (September 1, 2016): 191–200. http://dx.doi.org/10.1515/logos-2016-0020.

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Abstract Often analyses of depositional environments from sparse data result in poor interpretation, especially in multipartite depositional settings such as the Niger Delta. For instance, differentiating channel sandstones, heteroliths and mudstones within proximal environments from those of distal facies is difficult if interpretations rely solely on well log signatures. Therefore, in order to achieve an effective and efficient interpretation of the depositional conditions of a given unit, integrated tools must be applied such as matching core descriptions with wireline log signature. In the present paper cores of three wells from the Coastal Swamp depositional belt of the Niger Delta are examined in order to achieve full understanding of the depositional environments. The well sections comprise cross-bedded sandstones, heteroliths (coastal and lower shoreface) and mudstones that were laid down in wave, river and tidal processes. Interpretations were made from each data set comprising gamma ray logs, described sedimentological cores showing sedimentary features and ichnological characteristics; these were integrated to define the depositional settings. Some portions from one of the well sections reveal a blocky gamma ray well log signature instead of a coarsening-upward trend that characterises a shoreface setting while in other wells the signatures for heteroliths at some sections are bell blocky in shaped rather than serrated. Besides, heteroliths and mudstones within the proximal facies and those of distal facies were difficult to distinguish solely on well log signatures. However, interpretation based on sedimentology and ichnology of cores from these facies was used to correct these inconsistencies. It follows that depositional environment interpretation (especially in multifarious depositional environments such as the Niger Delta) should ideally be made together with other raw data for accuracy and those based solely on well log signatures should be treated with caution.
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Dissertations / Theses on the topic "Well log interpretation"

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Wong, Kok W. "A neural fuzzy approach for well log and hydrocyclone data interpretation." Thesis, Curtin University, 1999. http://hdl.handle.net/20.500.11937/1281.

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A novel data analysis approach that is automatic, self-learning and self-explained, and which provides accurate and reliable results is reported. The data analysis tool is capable of performing multivariate non-parametric regression analysis, as well as quantitative inferential analysis using predictive learning. Statistical approaches such as multiple regression or discriminant analysis are usually used to perform this kind of analysis. However, they lack universal capabilities and their success in any particular application is directly affected by the problem complexity.The approach employs the use of Artificial Neural Networks (ANNs) and Fuzzy Logic to perform the data analysis. The features of these two techniques are the means by which the developed data analysis approach has the ability to perform self-learning as well as allowing user interaction in the learning process. Further, they offer a means by which rules may be generated to assist human understanding of the learned analysis model, and so enable an analyst to include external knowledge.Two problems in the resource industry have been used to illustrate the proposed method, as these applications contain non-linearity in the data that is unknown and difficult to derive. They are well log data analysis in petroleum exploration and hydrocyclone data analysis in mineral processing. This research also explores how this proposed data analysis approach could enhance the analysis process for problems of this type.
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Wong, Kok W. "A neural fuzzy approach for well log and hydrocyclone data interpretation." Curtin University of Technology, School of Electrical and Computer Engineering, 1999. http://espace.library.curtin.edu.au:80/R/?func=dbin-jump-full&object_id=10344.

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A novel data analysis approach that is automatic, self-learning and self-explained, and which provides accurate and reliable results is reported. The data analysis tool is capable of performing multivariate non-parametric regression analysis, as well as quantitative inferential analysis using predictive learning. Statistical approaches such as multiple regression or discriminant analysis are usually used to perform this kind of analysis. However, they lack universal capabilities and their success in any particular application is directly affected by the problem complexity.The approach employs the use of Artificial Neural Networks (ANNs) and Fuzzy Logic to perform the data analysis. The features of these two techniques are the means by which the developed data analysis approach has the ability to perform self-learning as well as allowing user interaction in the learning process. Further, they offer a means by which rules may be generated to assist human understanding of the learned analysis model, and so enable an analyst to include external knowledge.Two problems in the resource industry have been used to illustrate the proposed method, as these applications contain non-linearity in the data that is unknown and difficult to derive. They are well log data analysis in petroleum exploration and hydrocyclone data analysis in mineral processing. This research also explores how this proposed data analysis approach could enhance the analysis process for problems of this type.
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Alborzi, Mahmood. "Application of neural networks to real-time log interpretation in oil well drilling." Thesis, Brunel University, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.309502.

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Javid, Sanaz. "Petrography and petrophysical well log interpretation for evaluation of sandstone reservoir quality in the Skalle well (Barents Sea)." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for geologi og bergteknikk, 2013. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-23137.

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39 thin sections and petrophysical log data from the Skalle well in the Hammerfest Basin, in the southwestern part of the Barents Sea, have been studied to interpret lithology, and diagenesis and their effect on the reservoir quality, and to compare reservoir properties of the different reservoir units. Petrophysical log data have been calibrated for reservoir description in cases where core material is not available. The studied formations are comprised by the Stø, Fuglen, Hekkingen, Knurr, Kolje and the Lower Kolmule Formations. The Knurr and Kolje Formations have been identified and interpreted only by wire line logs, as core material was not available for those intervals.The Lower Kolmule Formation of sandstones of lithic greywacke composition, and the Stø Formation with sandstones of subarkosic arenite composition are considered as possible reservoir rocks. All the formations are water filled which is reflected by the low resistivity logs responses. The mature sandstones of the Stø Formation show high reservoir quality (high porosity and permeability) compared to the Lower Kolmule Formation. The Hekkingen Formation is a potential source rock for the Lower Kolmule Formation, as well as a seal (cap rock) for the Stø Formation. Cementation, dissolution, compaction, clay mineral authigenesis and stylolitization are the most significant diagenetic processes affecting the reservoir quality. Some other type of processes such as glauconitization and bioturbation are also common in the studied well.
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Barker, Abram Max. "An Integrated Well Log and 3D Seismic Interpretation of Missourian Clinoforms, Osage County, Oklahoma." Thesis, University of Arkansas, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10981180.

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Integrated analysis of well and geophysical data can provide detailed geologic interpretation of the subsurface in Osage County, Oklahoma. Systems tracts and depositional system successions can be interpreted at marginal seismic resolution using well log motif with seismic reflector character within a depositional context. Shelf-prism and subaqueous, delta-scale clinoforms of Missourian age observed in 3D seismic were interpreted with greater sequence stratigraphic detail when coupled with wireline well logs. The Late Pennsylvanian Midcontinent Sea was thought to be approximately 150 feet average depth across the southern Midcontinent during the Missourian Stage, and deepen towards the Arkoma and Anadarko Basins to the south. Here we show that the Late Pennsylvanian Midcontinent Sea floor was in water depths greater than 600 feet and sloped to the southeast, toward major, southern basins, during the Missourian Stage in Osage County. Shelf-prism and delta scale clinoforms up to 600 and 300 feet of relief, respectively, were observed in paired seismic and well log cross sections, thickness maps, and structure maps dipping northwest at 052° strike, upon a basin floor dipping southeast at 253° strike. Lithologic and sequence stratigraphic interpretation revealed a mixed carbonate-siliciclastic system comprising of delta, offshore shelf, and carbonate buildup depositional systems of mesothem, 3rd order sequence magnitude. The observed succession included: 1) falling stage to lowstand, sand-prone, subaqueous delta, 2) transgressive to highstand offshore shelf and carbonate bank, and 3) falling stage delta. The depositional sucession demonstrates how carbonate banks related spatially to terrigenous sediment input in northeastern Oklahoma during the Late Pennsylvanian because of glacio-eustasy and possible tectonism.

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Graciolli, Vinicius Medeiros. "A novel classification method applied to well log data calibrated by ontology based core descriptions." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2018. http://hdl.handle.net/10183/174993.

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Um método para a detecção automática de tipos litológicos e contato entre camadas foi desenvolvido através de uma combinação de análise estatística de um conjunto de perfis geofísicos de poços convencionais, calibrado por descrições sistemáticas de testemunhos. O objetivo deste projeto é permitir a integração de dados de rocha em modelos de reservatório. Os testemunhos são descritos com o suporte de um sistema de nomenclatura baseado em ontologias que formaliza extensamente uma grande gama de atributos de rocha. As descrições são armazenadas em um banco de dados relacional junto com dados de perfis de poço convencionais de cada poço analisado. Esta estrutura permite definir protótipos de valores de perfil combinados para cada litologia reconhecida através do cálculo de média e dos valores de variância e covariância dos valores medidos por cada ferramenta de perfilagem para cada litologia descrita nos testemunhos. O algoritmo estatístico é capaz de aprender com cada novo testemunho e valor de log adicionado ao banco de dados, refinando progressivamente a identificação litológica. A detecção de contatos litológicos é realizada através da suavização de cada um dos perfis através da aplicação de duas médias móveis de diferentes tamanhos em cada um dos perfis. Os resultados de cada par de perfis suavizados são comparados, e as posições onde as linhas se cruzam definem profundidades onde ocorrem mudanças bruscas no valor do perfil, indicando uma potencial mudança de litologia. Os resultados da aplicação desse método em cada um dos perfis são então unificados em uma única avaliação de limites litológicos Os valores de média e variância-covariância derivados da correlação entre testemunhos e perfis são então utilizados na construção de uma distribuição gaussiana n-dimensional para cada uma das litologias reconhecidas. Neste ponto, probabilidades a priori também são calculadas para cada litologia. Estas distribuições são comparadas contra cada um dos intervalos litológicos previamente detectados por meio de uma função densidade de probabilidade, avaliando o quão perto o intervalo está de cada litologia e permitindo a atribuição de um tipo litológico para cada intervalo. O método desenvolvido foi testado em um grupo de poços da bacia de Sergipe- Alagoas, e a precisão da predição atingida durante os testes mostra-se superior a algoritmos clássicos de reconhecimento de padrões como redes neurais e classificadores KNN. O método desenvolvido foi então combinado com estes métodos clássicos em um sistema multi-agentes. Os resultados mostram um potencial significante para aplicação operacional efetiva na construção de modelos geológicos para a exploração e desenvolvimento de áreas com grande volume de dados de perfil e intervalos testemunhados.
A method for the automatic detection of lithological types and layer contacts was developed through the combined statistical analysis of a suite of conventional wireline logs, calibrated by the systematic description of cores. The intent of this project is to allow the integration of rock data into reservoir models. The cores are described with support of an ontology-based nomenclature system that extensively formalizes a large set of attributes of the rocks, including lithology, texture, primary and diagenetic composition and depositional, diagenetic and deformational structures. The descriptions are stored in a relational database along with the records of conventional wireline logs (gamma ray, resistivity, density, neutrons, sonic) of each analyzed well. This structure allows defining prototypes of combined log values for each lithology recognized, by calculating the mean and the variance-covariance values measured by each log tool for each of the lithologies described in the cores. The statistical algorithm is able to learn with each addition of described and logged core interval, in order to progressively refine the automatic lithological identification. The detection of lithological contacts is performed through the smoothing of each of the logs by the application of two moving means with different window sizes. The results of each pair of smoothed logs are compared, and the places where the lines cross define the locations where there are abrupt shifts in the values of each log, therefore potentially indicating a change of lithology. The results from applying this method to each log are then unified in a single assessment of lithological boundaries The mean and variance-covariance data derived from the core samples is then used to build an n-dimensional gaussian distribution for each of the lithologies recognized. At this point, Bayesian priors are also calculated for each lithology. These distributions are checked against each of the previously detected lithological intervals by means of a probability density function, evaluating how close the interval is to each lithology prototype and allowing the assignment of a lithological type to each interval. The developed method was tested in a set of wells in the Sergipe-Alagoas basin and the prediction accuracy achieved during testing is superior to classic pattern recognition methods such as neural networks and KNN classifiers. The method was then combined with neural networks and KNN classifiers into a multi-agent system. The results show significant potential for effective operational application to the construction of geological models for the exploration and development of areas with large volume of conventional wireline log data and representative cored intervals.
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Fanka, Walter Roye Taju. "Well Log and Seismic Data Interpretation : Rock Physics Study of Poorly Consolidated Sandstones in The North Sea." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for petroleumsteknologi og anvendt geofysikk, 2012. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-18608.

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We use rock physics models for poorly consolidated rocks to diagnose reservoir sandstones in the Alvheim Field, North Sea. Geological factors that will control the rock physics and seismic properties include clay content, sorting, diagenesis, mineralogy, and bedding configuration. The various geologic factors will affect the fluid and stress sensitivity in these rocks. We investigate the interrelationships between various geological factors and seismic fluid and stress sensitivity, by combining well log data and rock physics models. Finally, we determine inter-well characteristics in terms of varying geological factors at different locations and discuss the results in terms of expected seismic signatures in the area.
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Hulsey, Josiah D. "Applying modern interpretation techniques to old hydrocarbon fields to find new reserves: A case study in the onshore Gulf of Mexico, U.S.A." ScholarWorks@UNO, 2016. http://scholarworks.uno.edu/td/2160.

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This study shows how the use of modern geological investigative techniques can reopen old, “drained” hydrocarbon fields. Specifically, it looks at the White Castle Field in South Louisiana. This field has pay sections ranging from late Oligocene to late Miocene. The late Oligocene package is underexplored and understudied and contains 3 primary reservoirs (Cib Haz (CH), MW, and MR). This study established the depositional history of these reservoirs. During most of the late Oligocene, the White Castle Salt Dome was located in a minibasin on the continental slope. The CH and MW deposited in this minibasin. The CH is an amalgamation of slumped shelfal limestones, sandstones, and shales deposited during a lowstand systems tract (LST). The MW comprises a shelf-edge delta that is part of a LST. The MR is an incised valley fill located in the continental shelf that was deposited during LST after the minibasin was filled.
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Welder, Jennifer. "Seismic Interpretation and Well Log Analysis of Jay County, Indiana, focused on lithologic units below the Mt. Simon Formation." Wright State University / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=wright1421158261.

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Butterfield, Andrei. "Characterization of a Utica Shale Reflector Package Using Well Log Data and Amplitude Variation with Offset Analysis." Wright State University / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=wright1401462908.

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Books on the topic "Well log interpretation"

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Limited, Schlumberger. Log interpretation principles/applications. Houston: Schlumberger Educational Services, 1991.

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Doveton, John H. Geologic log interpretation: Reading the rocks from wireline logs. Tulsa, Okla: SEPM (Society for Sedimentary Geology), 1994.

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Bassiouni, Zaki. Theory, measurement, and interpretation of well logs. Richardson, TX: Henry L. Doherty Memorial Fund of AIME, Society of Petroleum Engineers, 1994.

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The geological interpretation of well logs. 2nd ed. Houston: Gulf Pub. Co., 1997.

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The geological interpretation of well logs. 2nd ed. Caithness: Whittles Publishing, 1996.

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The geological interpretation of well logs. Glasgow: Blackie, 1986.

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The geological interpretation of well logs. 2nd ed. Sutherland: Rider-French Consulting, 2002.

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The geological interpretation of well logs. Glasgow [Strathclyde]: Blackie, 1986.

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Sah, S. L. Encyclopaedia of petroleum science and engineering: Well logs interpretation, and fundamentals of palynology. Delhi: Kalpaz Publications, 2008.

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Strom, Eric W. Hydrogeologic interpretations of natural-gamma logs for 31 shallow wells in the Memphis, Tennessee, area. Jackson, Miss: U.S. Dept. of the Interior, U.S. Geological Survey, 1997.

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Book chapters on the topic "Well log interpretation"

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Ellis, Darwin V., and Julian M. Singer. "Introduction to Well Log Interpretation: Finding the Hydrocarbon." In Well Logging for Earth Scientists, 17–39. Dordrecht: Springer Netherlands, 2007. http://dx.doi.org/10.1007/978-1-4020-4602-5_2.

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Huang, L., D. Richers, and J. E. Robinson. "Well-Log Imaging and Its Application to Geologic Interpretation." In Computer Applications in the Earth Sciences, 163–84. Boston, MA: Springer US, 1993. http://dx.doi.org/10.1007/978-1-4615-2826-5_12.

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Bao, Liyuan, Xianjun Cao, Changjiang Yu, Guanwen Zhang, and Wei Zhou. "A Deep Neural Network Based Feature Learning Method for Well Log Interpretation." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 543–56. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-67514-1_43.

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Nurmi, Roy D. "8. Geologic Interpretation of Well Log and Seismic Measurements in Reservoirs Associated with Evaporites." In Evaporites and Hydrocarbons, edited by B. Charlotte Schreiber, 405–60. New York Chichester, West Sussex: Columbia University Press, 1988. http://dx.doi.org/10.7312/schr91060-009.

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Yu, Tina, and Dave Wilkinson. "A Co-Evolutionary Fuzzy System for Reservoir Well Logs Interpretation." In Evolutionary Computation in Practice, 199–218. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-75771-9_9.

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Konaté, Ahmed Amara, Heping Pan, Muhammad Adnan Khalid, Gang Li, Jie Huai Yang, Chengxiang Deng, and Sinan Fang. "Machine Learning Interpretation of Conventional Well Logs in Crystalline Rocks." In Advances in Swarm and Computational Intelligence, 360–70. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-20472-7_39.

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Wang, Chi-Yuen, and Michael Manga. "Groundwater Temperature." In Lecture Notes in Earth System Sciences, 231–56. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-64308-9_8.

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AbstractChanges of temperature in response to earthquakes have long been documented and, in the case where systematic patterns of change can be discerned, may reveal important hydrogeologic processes. Progress in our understanding of these processes, however, has been slow, largely because systematic measurements are relatively scarce. In this chapter we review some cases where earthquake-induced changes of groundwater temperature were documented and interpreted. More importantly, we show that most interpretations are under-constrained and accurate explanation of the measured changes is often difficult. In order to better constrain the interpretation, co-located measurement of groundwater flow from conductive fractures or formations intersecting the wells is needed to interpret temperature measurements. An often neglected mechanism is turbulent mixing of water in wells, which may occur frequently during earthquakes because the water column in a well at thermal equilibrium with the local geotherm is usually in a state of mechanical disequilibrium.
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Owen, Gwilym, Yu Chen, Gwilym Pryce, Tim Birabi, Hui Song, and Bifeng Wang. "Deprivation Indices in China: Establishing Principles for Application and Interpretation." In The Urban Book Series, 305–27. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-74544-8_14.

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AbstractIndicesofMultiple Deprivation(IMDs) aim to measure living standards at the small area level. These indices were originally developed in the United Kingdom, but there is a growing interest in adapting them for use in China. However, due to data limitations, Chinese deprivation indices sometimes diverge considerably in approaches and are not always connected with the underlying concepts within UK analysis. In this paper, we seek to bring direction and conceptual rigour to this nascent literature by establishing a set of core principles for IMD estimation that are relevant and feasible in the Chinese context. These principles are based on specifying deprivation domains from theory, selecting the most appropriate measurements for these domains, and then applying rigorous statistical techniques to combine them into an IMD. We apply these principles to create an IMD for Shijiazhuang, the capital city of Hebei Province. We use this to investigate the spatial patterns of deprivation in Shijiazhuang, focussing on clusteringand centralisationof deprivation as well as exploring different deprivation typologies. We highlight two distinct types of deprived areas. One is clustered in industrial areas on the edge of the city, while the second is found more centrally and contains high proportions of low-skilled service workers.
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Andreu-Hayles, Laia, Mathieu Lévesque, Rossella Guerrieri, Rolf T. W. Siegwolf, and Christian Körner. "Limits and Strengths of Tree-Ring Stable Isotopes." In Stable Isotopes in Tree Rings, 399–428. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-92698-4_14.

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AbstractThis chapter aims at summarizing strengths and caveats on the suitability of stable carbon and oxygen isotopes in tree rings as recorders for fingerprints of environmental influences. First, environmental constraints limiting tree growth and shaping tree species distribution worldwide are discussed. Second, examples are presented for environmental conditions under which tree-ring isotopes record environmental signals particularly well, but also cases where physiological processes can mask climate signals. Third, the link between leaf-level carbon assimilation and the investment of assimilates in the stem during the annual ring formation are discussed in light of the resulting deviations of the isotopic values between leaves and tree rings. Finally, difficulties and pitfalls in the interpretation of stable isotope signals in tree rings are reviewed. These problems often result from a poor understanding of when and how the tree canopy, stems and roots are physiologically interconnected. Current literature suggests that photosynthesis and radial growth are only loosely coupled, if at all, challenging the interpretation of environmental signals recorded in tree-ring isotopes. Harsh environmental conditions (e.g. low temperatures, drought) often result in a decoupling of carbon assimilation and growth. The chapter closes by providing possible solutions on how to improve the detection of environmental information from stable isotope signals by integrating scales and different methodological approaches.
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Pastoors, Andreas, and Tilman Lenssen-Erz. "Introduction." In Reading Prehistoric Human Tracks, 1–11. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-60406-6_1.

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AbstractThis book explains that after long periods of prehistoric research in which the importance of the archaeological as well as the natural context of rock art has been constantly underestimated, research has now begun to take this context into focus for documentation, analysis, interpretation and understanding. Human footprints are prominent among the long-time under-researched features of the context in caves with rock art. In order to compensate for this neglect an innovative research program has been established several years ago that focuses on the merging of indigenous knowledge and western archaeological science for the benefit of both sides. The book composes first the methodological diversity in the analysis of human tracks. Here major representatives of anthropological, statistical and traditional approaches feature the multi-layered methods available for the analysis of human tracks. It second compiles case studies from around the globe of prehistoric human. For the first time the most important sites which have been found worldwide are published in a single publication. The third focus of this book is on first hand experiences of researchers with indigenous tracking experts from around the globe, expounding on how archaeological science can benefit from the ancestral knowledge.
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Conference papers on the topic "Well log interpretation"

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Al Shekaili, Fatema, Soman Chacko, Samy Serag El Din, Yahui Yin, Aurelie Pujol, and Gael Lecante. "Well log Conditioning for Quantitative Seismic Interpretation." In Abu Dhabi International Petroleum Conference and Exhibition. Society of Petroleum Engineers, 2012. http://dx.doi.org/10.2118/161382-ms.

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Zhang, Lin, and Mary M. Poulton. "Neural Network Interpretation of EM39 Well Log Data." In Symposium on the Application of Geophysics to Engineering and Environmental Problems 1997. Environment and Engineering Geophysical Society, 1997. http://dx.doi.org/10.4133/1.2922394.

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Kozhevnikov, Dmitry, and Kazimir Kovalenko. "Petrophysical Invariance Principle in Adaptive Well Log Interpretation." In SPE Russian Oil and Gas Conference and Exhibition. Society of Petroleum Engineers, 2010. http://dx.doi.org/10.2118/135977-ms.

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Verga, F., D. Viberti, and M. Gonfalini. "Uncertainty Propagation in the Well Log Interpretation Process." In ECMOR VIII - 8th European Conference on the Mathematics of Oil Recovery. European Association of Geoscientists & Engineers, 2002. http://dx.doi.org/10.3997/2214-4609.201405960.

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Gupta, Aarushi, and Utkarsh Soumya. "Well Log Interpretation Using Deep Learning Neural Networks." In International Petroleum Technology Conference. International Petroleum Technology Conference, 2020. http://dx.doi.org/10.2523/iptc-19678-abstract.

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Uspenskaya, L. A., D. V. Emelyanov, A. P. Kulik, D. A. Garenskih, and A. A. Belomestnykh. "Rock Physics Modelling for Successful Well-log Interpretation." In Saint Petersburg 2012. Netherlands: EAGE Publications BV, 2012. http://dx.doi.org/10.3997/2214-4609.20143685.

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Zhang, Lin, and Mary M. Poulton. "Neural Network Interpretation Of Em39 Well Log Data." In 10th EEGS Symposium on the Application of Geophysics to Engineering and Environmental Problems. European Association of Geoscientists & Engineers, 1997. http://dx.doi.org/10.3997/2214-4609-pdb.204.1997_023.

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Walsh, J. W., S. L. Brown, and G. B. Asquith. "Analyzing Well Logs From the Montoya Lime Using a New Carbonate Well Log Interpretation Procedure." In Permian Basin Oil and Gas Recovery Conference. Society of Petroleum Engineers, 1994. http://dx.doi.org/10.2118/27645-ms.

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Katterbauer, Klemens, Ali A. Al-Yousif, and Alberto Marsala. "Intelligent Reconciliation of Well Logs – A Pathway Towards 4IR Assisted Log Interpretation." In Abu Dhabi International Petroleum Exhibition & Conference. Society of Petroleum Engineers, 2020. http://dx.doi.org/10.2118/202621-ms.

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Kozhevnikov, Dmitry, Kazimir Kovalenko, and Ivan Sergeevich Deshenenkov. "The Adaptive Well Log Data Interpretation in Geological Modeling." In SPE Europec/EAGE Annual Conference. Society of Petroleum Engineers, 2012. http://dx.doi.org/10.2118/152463-ms.

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Reports on the topic "Well log interpretation"

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Miyairi, M., K. Akihisa, T. Uchida, T. S. Collett, and S R Dallimore. Well-log interpretation of gas-hydrate-bearing formations in the JAPEX/JNOC/GSC Mallik 2L-38 gas hydrate research well. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1999. http://dx.doi.org/10.4095/210771.

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Wang, L., D. S. Edwards, A. Bailey, L. K. Carr, C. J. Boreham, E. Grosjean, J. Anderson, et al. Well log data analysis and interpretation on the pre-Carboniferous succession in Waukarlycarly 1, Canning Basin, Western Australia. Geoscience Australia, 2021. http://dx.doi.org/10.11636/record.2021.003.

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Carlos Torres-Verdin and Mrinal K. Sen. INTEGRATED APPROACH FOR THE PETROPHYSICAL INTERPRETATION OF POST-AND PRE-STACK 3-D SEISMIC DATA, WELL-LOG DATA, CORE DATA, GEOLOGICAL INFORMATION AND RESERVOIR PRODUCTION DATA VIA BAYESIAN STOCHASTIC INVERSION. Office of Scientific and Technical Information (OSTI), September 2004. http://dx.doi.org/10.2172/837074.

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Carlos Torres-Verdin and Mrinal K. Sen. INTEGRATED APPROACH FOR THE PETROPHYSICAL INTERPRETATION OF POST- AND PRE-STACK 3-D SEISMIC DATA, WELL-LOG DATA, CORE DATA, GEOLOGICAL INFORMATION AND RESERVOIR PRODUCTION DATA VIA BAYESIAN STOCHASTIC INVERSION. Office of Scientific and Technical Information (OSTI), March 2004. http://dx.doi.org/10.2172/825256.

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Hu, K., and D. Lavoie. Porosity and permeability evaluation and geological interpretations from core data and geophysical well logs for 18 wells in the Paleozoic successions of eastern Canada and implications for hydrocarbon exploration. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2008. http://dx.doi.org/10.4095/224832.

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Karstensen, Johannes, Alexandra Andrae, Ludwig Bitzan, Jakob Deutloff, Christiane Lösel, Paul J. Witting, Nils O. Niebaum, et al. Student cruise: Observing techniques for Physical Oceanographers Cruise No. AL529. GEOMAR, 2020. http://dx.doi.org/10.3289/cr_al529.

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Oct. 07 2019 – Oct. 10, 2019 Kiel (Germany) – Kiel (Germany) MNF-Pher-110The main purpose of the ALKOR cruise AL529 was the training of students in observational techniques applied by physical oceanographers. The students who participated in the trip attend the module "Measurement Methods of Oceanography" which is offered in the Bachelor program "Physics of the Earth System" at CAU Kiel. During the AL529 the students were instructed in instrument calibration and in the interpretation of measurement data at sea. In addition, the students had the opportunity to learn about working and living at sea and to explore and study the impact of physical processes in the western Baltic Sea, the sea at their doorstep. The observations show a quasi-synoptic picture of the hydrography and currents in the western Baltic Sea. Twice-repeated hydrographic and current sections across the Fehmarn Belt show well the short time scales where significant changes occur. A zonal section along the deepest topography, from about 10°40'E to 014°21'E, shows very nicely the two-layer system of outflowing low salinity and inflowing North Sea water. A bottom shield anchorage shows the currents in the water column and the near-bottom temperature and salinity variations in the Fehmarnbelt area.
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Kelly, Luke. Emerging Trends Within the Women, Peace and Security (WPS) Agenda. Institute of Development Studies (IDS), January 2022. http://dx.doi.org/10.19088/k4d.2022.019.

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This report has identified emerging issues within the women, peace and security (WPS) agenda. Climate change has long been identified as a key cross-cutting issue and several potential avenues for WPS policy are identified. Other issues such as artificial intelligence (AI) have been highlighted as potentially relevant, but relatively little discussed with respect to WPS. The WPS agenda focuses on addressing the gendered impact of conflict and seeking to prevent conflict through increased women’s participation. In this report, WPS is understood as a body of UN Security Council resolutions (UNSCRs) and state national action plans (NAPs) labelled as WPS; as well as other UN and state policies using the language and ideas of WPS; and actions and ideas produced by civil society and academics inspired by the United Nations (UN) agenda or sharing ideas with it. The report focuses on new and emerging issues identified by academics and policymakers as relevant to the WPS agenda. Emerging trends and issues are broadly understood as: • Parts of the WPS agenda that are increasingly part of policies formulated by the UN, member states or civil society actors. • Parts of the WPS agenda that scholars or policymakers think have been neglected or not implemented sufficiently. • Re-interpretations of the framing of the WPS agenda. • New areas to which it is argued WPS should be applied. • Parallel international policy agendas with conceptual or legislative overlap with WPS. Emerging trends and issues are discussed with reference to their status in policy and implementation; normative debates about their place in the WPS agenda; and evidence on their implications for and applicability to certain contexts. The report does not seek to predict or assess the future trends or their relative importance, beyond highlighted existing interpretations of their status, implementation and potential implications. The report discusses a variety of emerging issues. These include issues where the WPS agenda has already been applied, but where its implementation –or lack thereof – has been criticised, such as in counterterrorism and arms control, or the conceptualisation of gender. The ability of WPS instruments to address changing forms of conflict has also been criticised. Issues to which it is argued that WPS should, and could, be applied more thoroughly, such as gang violence and trafficking, are discussed. The report includes new fields such as cybersecurity and AI, about which there is relatively little literature linked to WPS, but agreement that it may be relevant.
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Dickman, Martin B., and Oded Yarden. Involvement of the PKA and MAPK signal transduction pathways in sclerotial morphogenesis in Sclerotinia sclerotiorum. United States Department of Agriculture, September 2007. http://dx.doi.org/10.32747/2007.7695861.bard.

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The long-term goals of our research are to understand the regulation of sclerotial development and pathogenicity in S. sclerotiorum. The focus in this project is on the elucidation of the signaling events and environmental cues involved in the regulation of these processes, utilizing and continuously developing tools our research groups have established and/or adapted for analysis of S. sclerotiorum. Our stated specific objectives were to: 1. Follow activities and function of S. sclerotiorumPKA. 2. Identify and functionally evaluate effectors of the S. sclerotiorumERK-likeMAPK signaling pathway. 3. Perform structural and functional analysis of genes whose expression is altered under conditions affecting either PKA and/or MAPK. As can be seen below, we have not only met most of the listed goals, but have also expanded our research. We have been working both together and in parallel in order to advance our goals. We have jointly shown how an ERK-likeMAPK is required sclerotia formation. We have analyzed, in parallel, the involvement of PKA in sclerotiogenesis and, interestingly, have reached some overlapping results but each group has provided a slightly different interpretation to the picture obtained. It will be interesting to see how this aspect of the analysis progresses, as we jointly tackle the yet unresloved issues. We have also made progress on the analysis of ser/thr phosphatases (specifically – calcineurin, which has been reported to interact with PKA) and PP2A in S. sclerotiorum as well as the S. sclerotiorum rasgene, which we have cloned and shown induces SMK1, the ERK-like kinase responsible for sclerotia formation. In addition to the time and efforts invested towards reaching the specific goals mentioned, both PIs are actively involved in a major international effort to sequence and annotate the entire S. sclerotiorum genome. Though time consuming (and perhaps requiring divergence of some time and resources from the original workplan), we have given this topic a very high priority to this effort as the long term implications of the success of this venture are enormous.
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Delwiche, Michael, Boaz Zion, Robert BonDurant, Judith Rishpon, Ephraim Maltz, and Miriam Rosenberg. Biosensors for On-Line Measurement of Reproductive Hormones and Milk Proteins to Improve Dairy Herd Management. United States Department of Agriculture, February 2001. http://dx.doi.org/10.32747/2001.7573998.bard.

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The original objectives of this research project were to: (1) develop immunoassays, photometric sensors, and electrochemical sensors for real-time measurement of progesterone and estradiol in milk, (2) develop biosensors for measurement of caseins in milk, and (3) integrate and adapt these sensor technologies to create an automated electronic sensing system for operation in dairy parlors during milking. The overall direction of research was not changed, although the work was expanded to include other milk components such as urea and lactose. A second generation biosensor for on-line measurement of bovine progesterone was designed and tested. Anti-progesterone antibody was coated on small disks of nitrocellulose membrane, which were inserted in the reaction chamber prior to testing, and a real-time assay was developed. The biosensor was designed using micropumps and valves under computer control, and assayed fluid volumes on the order of 1 ml. An automated sampler was designed to draw a test volume of milk from the long milk tube using a 4-way pinch valve. The system could execute a measurement cycle in about 10 min. Progesterone could be measured at concentrations low enough to distinguish luteal-phase from follicular-phase cows. The potential of the sensor to detect actual ovulatory events was compared with standard methods of estrus detection, including human observation and an activity monitor. The biosensor correctly identified all ovulatory events during its testperiod, but the variability at low progesterone concentrations triggered some false positives. Direct on-line measurement and intelligent interpretation of reproductive hormone profiles offers the potential for substantial improvement in reproductive management. A simple potentiometric method for measurement of milk protein was developed and tested. The method was based on the fact that proteins bind iodine. When proteins are added to a solution of the redox couple iodine/iodide (I-I2), the concentration of free iodine is changed and, as a consequence, the potential between two electrodes immersed in the solution is changed. The method worked well with analytical casein solutions and accurately measured concentrations of analytical caseins added to fresh milk. When tested with actual milk samples, the correlation between the sensor readings and the reference lab results (of both total proteins and casein content) was inferior to that of analytical casein. A number of different technologies were explored for the analysis of milk urea, and a manometric technique was selected for the final design. In the new sensor, urea in the sample was hydrolyzed to ammonium and carbonate by the enzyme urease, and subsequent shaking of the sample with citric acid in a sealed cell allowed urea to be estimated as a change in partial pressure of carbon dioxide. The pressure change in the cell was measured with a miniature piezoresistive pressure sensor, and effects of background dissolved gases and vapor pressures were corrected for by repeating the measurement of pressure developed in the sample without the addition of urease. Results were accurate in the physiological range of milk, the assay was faster than the typical milking period, and no toxic reagents were required. A sampling device was designed and built to passively draw milk from the long milk tube in the parlor. An electrochemical sensor for lactose was developed starting with a three-cascaded-enzyme sensor, evolving into two enzymes and CO2[Fe (CN)6] as a mediator, and then into a microflow injection system using poly-osmium modified screen-printed electrodes. The sensor was designed to serve multiple milking positions, using a manifold valve, a sampling valve, and two pumps. Disposable screen-printed electrodes with enzymatic membranes were used. The sensor was optimized for electrode coating components, flow rate, pH, and sample size, and the results correlated well (r2= 0.967) with known lactose concentrations.
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Stall, Nathan M., Kevin A. Brown, Antonina Maltsev, Aaron Jones, Andrew P. Costa, Vanessa Allen, Adalsteinn D. Brown, et al. COVID-19 and Ontario’s Long-Term Care Homes. Ontario COVID-19 Science Advisory Table, January 2021. http://dx.doi.org/10.47326/ocsat.2021.02.07.1.0.

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Key Message Ontario long-term care (LTC) home residents have experienced disproportionately high morbidity and mortality, both from COVID-19 and from the conditions associated with the COVID-19 pandemic. There are several measures that could be effective in preventing COVID-19 outbreaks, hospitalizations, and deaths in Ontario’s LTC homes, if implemented. First, temporary staffing could be minimized by improving staff working conditions. Second, homes could be further decrowded by a continued disallowance of three- and four-resident rooms and additional temporary housing for the most crowded homes. Third, the risk of SARS-CoV-2 infection in staff could be minimized by approaches that reduce the risk of transmission in communities with a high burden of COVID-19. Summary Background The Province of Ontario has 626 licensed LTC homes and 77,257 long-stay beds; 58% of homes are privately owned, 24% are non-profit/charitable, 16% are municipal. LTC homes were strongly affected during Ontario’s first and second waves of the COVID-19 pandemic. Questions What do we know about the first and second waves of COVID-19 in Ontario LTC homes? Which risk factors are associated with COVID-19 outbreaks in Ontario LTC homes and the extent and death rates associated with outbreaks? What has been the impact of the COVID-19 pandemic on the general health and wellbeing of LTC residents? How has the existing Ontario evidence on COVID-19 in LTC settings been used to support public health interventions and policy changes in these settings? What are the further measures that could be effective in preventing COVID-19 outbreaks, hospitalizations, and deaths in Ontario’s LTC homes? Findings As of January 14, 2021, a total of 3,211 Ontario LTC home residents have died of COVID-19, totaling 60.7% of all 5,289 COVID-19 deaths in Ontario to date. There have now been more cumulative LTC home outbreaks during the second wave as compared with the first wave. The infection and death rates among LTC residents have been lower during the second wave, as compared with the first wave, and a greater number of LTC outbreaks have involved only staff infections. The growth rate of SARS-CoV-2 infections among LTC residents was slower during the first two months of the second wave in September and October 2020, as compared with the first wave. However, the growth rate after the two-month mark is comparatively faster during the second wave. The majority of second wave infections and deaths in LTC homes have occurred between December 1, 2020, and January 14, 2021 (most recent date of data extraction prior to publication). This highlights the recent intensification of the COVID-19 pandemic in LTC homes that has mirrored the recent increase in community transmission of SARS-CoV-2 across Ontario. Evidence from Ontario demonstrates that the risk factors for SARS-CoV-2 outbreaks and subsequent deaths in LTC are distinct from the risk factors for outbreaks and deaths in the community (Figure 1). The most important risk factors for whether a LTC home will experience an outbreak is the daily incidence of SARS-CoV-2 infections in the communities surrounding the home and the occurrence of staff infections. The most important risk factors for the magnitude of an outbreak and the number of resulting resident deaths are older design, chain ownership, and crowding. Figure 1. Anatomy of Outbreaks and Spread of COVID-19 in LTC Homes and Among Residents Figure from Peter Hamilton, personal communication. Many Ontario LTC home residents have experienced severe and potentially irreversible physical, cognitive, psychological, and functional declines as a result of precautionary public health interventions imposed on homes, such as limiting access to general visitors and essential caregivers, resident absences, and group activities. There has also been an increase in the prescribing of psychoactive drugs to Ontario LTC residents. The accumulating evidence on COVID-19 in Ontario’s LTC homes has been leveraged in several ways to support public health interventions and policy during the pandemic. Ontario evidence showed that SARS-CoV-2 infections among LTC staff was associated with subsequent COVID-19 deaths among LTC residents, which motivated a public order to restrict LTC staff from working in more than one LTC home in the first wave. Emerging Ontario evidence on risk factors for LTC home outbreaks and deaths has been incorporated into provincial pandemic surveillance tools. Public health directives now attempt to limit crowding in LTC homes by restricting occupancy to two residents per room. The LTC visitor policy was also revised to designate a maximum of two essential caregivers who can visit residents without time limits, including when a home is experiencing an outbreak. Several further measures could be effective in preventing COVID-19 outbreaks, hospitalizations, and deaths in Ontario’s LTC homes. First, temporary staffing could be minimized by improving staff working conditions. Second, the risk of SARS-CoV-2 infection in staff could be minimized by measures that reduce the risk of transmission in communities with a high burden of COVID-19. Third, LTC homes could be further decrowded by a continued disallowance of three- and four-resident rooms and additional temporary housing for the most crowded homes. Other important issues include improved prevention and detection of SARS-CoV-2 infection in LTC staff, enhanced infection prevention and control (IPAC) capacity within the LTC homes, a more balanced and nuanced approach to public health measures and IPAC strategies in LTC homes, strategies to promote vaccine acceptance amongst residents and staff, and further improving data collection on LTC homes, residents, staff, visitors and essential caregivers for the duration of the COVID-19 pandemic. Interpretation Comparisons of the first and second waves of the COVID-19 pandemic in the LTC setting reveal improvement in some but not all epidemiological indicators. Despite this, the second wave is now intensifying within LTC homes and without action we will likely experience a substantial additional loss of life before the widespread administration and time-dependent maximal effectiveness of COVID-19 vaccines. The predictors of outbreaks, the spread of infection, and deaths in Ontario’s LTC homes are well documented and have remained unchanged between the first and the second wave. Some of the evidence on COVID-19 in Ontario’s LTC homes has been effectively leveraged to support public health interventions and policies. Several further measures, if implemented, have the potential to prevent additional LTC home COVID-19 outbreaks and deaths.
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