scholarly journals Real-Time Data Transmission and Visualization as a Powerful Technology to Reduce Non-Productive Time During Drilling Operations: Present Day Capabilities, Limitation, and Future Development

2020 ◽  
Vol 43 (3) ◽  
pp. 135-142
Author(s):  
Yustian Ekky Rahanjani ◽  
Budhi Nugraha
Keyword(s):  
Real Time ◽  
Data Transmission ◽  
Network Connectivity ◽  
Local Network ◽  
Time Data ◽  
Literature Study ◽  
Intelligence System ◽  
Real Time Data ◽  
Drilling Operations ◽  
Productive Time

This paper primarily is focusing on presenting the non-productive time overview and any kind of non-productive time that can be reduced by real-time data technology, real-time data transmission and visualization infrastructure which supports the processes of aggregation, transmission, and visualization; the example of multipurpose implementation and further innovation and improvements that can be made within the real-time data transmission and visualization, such as real-time reservoir footage calculation during geosteering and drill-time calculation to pick the formation tops and casing point; the challenges and limitation while using real-time data, such as VSAT and local network connectivity issue; and future target and improvement of real-time data usage especially to make an artifi cial intelligence system to predict the potential feature, such as formation or drilling problem while drilling. All of those stuff s could be found by literature study and direct professional experience while handling real-time data system. This technology will inspire the user to design their own solution for their operations. Despite the signifi cant advances on real-time data transmission and visualization, there is signifi cant room to fully use itspotential for advanced workfl ows and the usage of real-time data technology which was proven to reduce the Non-Productive Time that could save the operational cost. We believe that the utilization of real-time data transmission and visualization will defi nitely increase the effi ciency of the drilling operations, especially for multiple wells operations.

Turbodrill Bottomhole Assembly and Real-Time Data Improve Through-Tubing Coiled-Tubing Drilling Operations in Sour Gas Well

2015 ◽  
Author(s):  
A. Ebrahimi ◽  
P. J. Schermer ◽  
W. Jelinek ◽  
D. Pommier ◽  
S. Pfeil ◽  
...  
Keyword(s):  
Real Time ◽  
Time Data ◽  
Gas Well ◽  
Coiled Tubing ◽  
Real Time Data ◽  
Drilling Operations ◽  
Sour Gas

Real Time Data: Interactive Monitoring of Data Flow for Continuous and Reliable Data Transmission

2013 ◽  
Author(s):  
Abdulrahman A. Al-Amer ◽  
Muhammad Al-Gosayir ◽  
Naser Al-Naser ◽  
Hussain Al-Towaileb
Keyword(s):  
Real Time ◽  
Data Transmission ◽  
Data Flow ◽  
Reliable Data ◽  
Time Data ◽  
Real Time Data

scholarly journals QoS Management for Embedded Databases in Multicore-Based Embedded Systems

2015 ◽  
Vol 2015 ◽  
pp. 1-14 ◽  
Author(s):  
Woochul Kang ◽  
Jaeyong Chung
Keyword(s):  
Embedded Systems ◽  
Real Time ◽  
Control Method ◽  
Network Connectivity ◽  
Time Data ◽  
Quality Of Data ◽  
Multiple Control ◽  
Data Intensive ◽  
Real Time Data

With ubiquitous deployment of sensors and network connectivity, amounts of real-time data for embedded systems are increasing rapidly and database capability is required for many embedded systems for systematic management of real-time data. In such embedded systems, supporting the timeliness of tasks accessing databases is an important problem. However, recent multicore-based embedded architectures pose a significant challenge for such data-intensive real-time tasks since the response time of accessing data can be significantly affected by potential intercore interferences. In this paper, we propose a novel feedback control scheme that supports the timeliness of data-intensive tasks against unpredictable intercore interferences. In particular, we use multiple inputs/multiple outputs (MIMO) control method that exploits multiple control knobs, for example, CPU frequency and the Quality-of-Data (QoD) to handle highly unpredictable workloads in multicore systems. Experimental results, using actual implementation, show that the proposed approach achieves the target Quality-of-Service (QoS) goals, such as task timeliness and Quality-of-Data (QoD) while consuming less energy compared to baseline approaches.

Season Cycling Gas Storage in Stogit Fields. A Real-Time Data Transmission System

2021 ◽  
Author(s):  
Graciela Eva Naveda ◽  
France Dominique Louie ◽  
Corinna Locatelli ◽  
Julien Davard ◽  
Sara Fragassi ◽  
...  
Keyword(s):  
Natural Gas ◽  
Real Time ◽  
Fiber Optics ◽  
Data Transmission ◽  
Distribution Networks ◽  
Gas Storage ◽  
Transmission System ◽  
Lessons Learned ◽  
Time Data ◽  
Real Time Data

Abstract Natural gas has become one of the major sources of energy for homes, public buildings and businesses, therefore gas storage is particularly important to ensure continuous provision compensating the differences between supply and demand. Stogit, part of Snam group, has been carrying out gas storage activities since early 1960's. Natural gas is usually stored underground, in large storage reservoirs. The gas is injected into the porous rock of depleted reservoirs bringing the reservoir nearby to its original condition. Injected gas can be withdrawn depending on the need. Gas market demands for industries and homes in Italy are mostly guaranteed from those Stogit reservoirs even in periods when imports are in crisis. Typically, from April to October, the gas is injected in these natural reservoirs that are "geologically tested"; while from November to March, gas is extracted from the same reservoirs and pumped into the distribution networks to meet the higher consumer demand.  Thirty-eight (38) wells, across nine (9) depleted fields, are completed with downhole quartz gauges and some of them with fiber-optics gauges. Downhole gauges are installed to continuously measure and record temperature and pressure from multiple reservoirs. The Real Time data system installed for 29 wells is used to collect, transmit and make available downhole data to Stogit (Snam) headquarter office. Data is automatically collected from remote terminal units (RTUs) and transferred over Stogit (Snam) network. The entire system works autonomously and has the capability of being remotely managed from anywhere over the corporate Stogit (Snam) IT network. Historical trends, including fiber optics gauges ones, are visualized and data sets could be retrieved using a fast and user-friendly software that enables data import into interpretation and reservoir modeling software. The use of this data collection and transmission system, versus the traditional manual download, brought timely data delivery to multiple users, coupled with improved personnel safety since land travels were eliminated. The following pages describe the case study, lessons learned, and integrated new practices used to improve the current and future data transmission deployments.

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