Extending Collective Operations with Application Semantics for Improving Multi-Cluster Performance

Author(s):  
L.A. Bongo ◽  
O. Anshus ◽  
J.M. Bjorndalen ◽  
T. Larsen
2021 ◽  
Author(s):  
Yegor Se ◽  
◽  
Michael Sullivan ◽  
Vahid Tohidi ◽  
Michael Lazorek ◽  
...  

The well design with long lateral section and multistage frac completion has been proven effective for development of the unconventional reservoirs. Top-tier well production in unconventional reservoir can be achieved by optimizing hydraulic completion and stimulation design, which necessitates an understanding of flow behavior and hydrocarbon contribution allocation.  Historically, conventional production logging (PL) surveys were scarcely used in unconventional reservoirs due to limited and often expensive conveyance options, as well as complicated and non-unique inflow interpretations caused by intricate and changing multi-phase flow behavior (Prakash et al., 2008). The assessment of the cluster performance gradually shifted towards distributed acoustic (DAS) and temperature (DTS) sensing methods using fiber optics cable, which continuously gained popularity in the industry. Fiber optics measurements were anticipated to generate production profiles along the lateral with sub-cluster resolution to assist with optimal completions design selection. Encapsulation of the fiber in the carbon rod provided alternative conveyance method for retrievable DFO measurements, which gained popularity due to cost-efficiency and operational convenience (Gardner et al., 2015). Recent utilization of micro-sensor technology in PL tools, (Abbassi et al, 2018, Donovan et al, 2019) allowed dramatic reduction of the size and the weight of the PL toolstring without compromising wellbore coverage by sensor array. Such ultra-compact PL toolstring could utilize the carbon rod as a taxi and provide mutually beneficial and innovative surveillance combination to evaluate production profile in the unconventional reservoirs. Array holdup and velocity measurements across wellbore from PL would reveal more details regarding multi-phase flow behavior, which could be used for cross-validation and constraining of production inflow interpretation based on DFO measurements. This paper summarizes the lessons learned, key observations and best practices from the unique 4 well program, where such innovative combination was tested in gas rich Duvernay shale reservoir.


2022 ◽  
Vol 27 (2) ◽  
pp. 1-33
Author(s):  
Liu Liu ◽  
Sibren Isaacman ◽  
Ulrich Kremer

Many embedded environments require applications to produce outcomes under different, potentially changing, resource constraints. Relaxing application semantics through approximations enables trading off resource usage for outcome quality. Although quality is a highly subjective notion, previous work assumes given, fixed low-level quality metrics that often lack a strong correlation to a user’s higher-level quality experience. Users may also change their minds with respect to their quality expectations depending on the resource budgets they are willing to dedicate to an execution. This motivates the need for an adaptive application framework where users provide execution budgets and a customized quality notion. This article presents a novel adaptive program graph representation that enables user-level, customizable quality based on basic quality aspects defined by application developers. Developers also define application configuration spaces, with possible customization to eliminate undesirable configurations. At runtime, the graph enables the dynamic selection of the configuration with maximal customized quality within the user-provided resource budget. An adaptive application framework based on our novel graph representation has been implemented on Android and Linux platforms and evaluated on eight benchmark programs, four with fully customizable quality. Using custom quality instead of the default quality, users may improve their subjective quality experience value by up to 3.59×, with 1.76× on average under different resource constraints. Developers are able to exploit their application structure knowledge to define configuration spaces that are on average 68.7% smaller as compared to existing, structure-oblivious approaches. The overhead of dynamic reconfiguration averages less than 1.84% of the overall application execution time.


2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sandra Bergamini Leonardo ◽  
Marco Antonio Pinheiro Silveira ◽  
Paloma María Teresa Martinez-Sánchez ◽  
Maria do Carmo Romeiro

PurposeThis paper aimed to analyze the contribution of the interorganizational relationship (IOR) factors trust and knowledge resources to the relational and transactional performance of a Brazilian agricultural cluster formed by small farmers.Design/methodology/approachA survey was conducted using a questionnaire divided into groups of variables, each group seeking to identify one of the three constructs: trust, knowledge resources and relational and transactional performance. A theoretical framework was elaborated and later compared with survey results, which were analyzed using exploratory factor analysis (EFA) and partial least squares–structural equation modeling (PLS-SEM).FindingsCorrelations between trust and relational and transactional cluster performance varied according to actors involved, being significant between some actors and not significant between others. Knowledge resources, on the other hand, proved to be significantly relevant for cluster performance, considering both relational and transactional measures.Research limitations/implicationsIt was made in a Brazilian single cluster and its conclusions cannot be generalized.Practical implicationsFarmers cannot innovate with the efficiency and effectiveness that the process demands. They need complementary capacity that apparently is not in the agricultural cluster. Research and development involve knowledge and techniques that empirical knowledge alone may not provide. And much of the formal knowledge is embedded in universities and research institutes. If there were investments by public entities in research and development to improve the culture and its by-products, this could contribute to improving the income of farmers.Social implicationsThis study provided a photograph of the current scenario of a Brazilian agricultural cluster. Changes in trust and knowledge resources could affect cluster relational and transactional performance. Special attention is deserved to the important role of scientific research on agricultural clusters to strengthen the capacity of critical analysis by the researcher who, with the results in hand, makes them public, hoping that the shared information can contribute with the research of other scholars and improve the quality of life of farmers involved.Originality/valueThis study offers empirical evidence that trust and knowledge resources can contribute to a Brazilian agricultural cluster performance, which can be analyzed considering both relational and transactional measures. These findings brought new fact to Singh and Shrivastava’s (2013) research.


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