2021 ◽  
Author(s):  
John E. McCormick ◽  
Yanghua Xiang ◽  
Matt Tourigny ◽  
Kevin J. Hollerich ◽  
Aaron Berarducci ◽  
...  

Abstract Completions operations, especially in modern day extended laterals, presents challenges related to tripping to total depth, applying weight down and pull up, and rotating. As dozens of stages in laterals exceeding 10,000 ft stepout have become frequent, numerous technologies have risen to assist with pushing the envelope for reliable completions operations in these long laterals. This paper examines a combination of three technologies that are more commonly being applied when drilling out frac plugs in long horizontals in the USA: hydraulic completion units, torque and drag software, and data acquisition systems. Coiled tubing units (CTU) have historically been used to drill out frac plugs in shorter horizontal shale wells for the last two decades, and where coil has mechanical limitations, Hydraulic Completion Units (HCU) have taken over drilling out frac plugs in the longer laterals of >10,000 ft. As the limits of drilling out frac plugs have been tested for HCUs, accurate real time data has enabled the crews to make the most of their equipment to reliably complete wells with longer and longer lateral sections. Torque and drag software modeling is a tool commonly used to predict axial force and torsional values during completions that result in the available hook load and the rotary torque requirements. The largest unknown in the planning phase is the appropriate friction factor to use for the upcoming well, with accurate friction factor prediction therefore the key to accurate prejob analysis. As of 2019 remote telemetry data acquisition systems (DAS) have been used on the HCUs, which has allowed key performance indicators (KPIs) to be automatically calculated. The program provides live feed to the service company and operator so that real time changes can be made if necessary. In addition to tracking KPIs in real time to provide the field crew positive or negative feedback, friction factors can be matched to predictive torque plots to identify trends prior to problems arising. Post-job analysis is needed to produce accurate predictive friction factors for future offset wells. The two main components to a successful post-job analysis are a software model that correctly represents the prior wellbore operations and accurate field data to compare with that model. Unfortunately, the software models in use are commonly limited by necessary assumptions with input data, such as rotary speed and tripping speed, and field data collected for comparison is often rudimentary. Experienced field personnel using engineering best practices can make use of current tools in combination to overcome the limitations commonly inhibiting accurate performance planning and predictive modeling. The inclusion of the DAS present on the HCU has greatly enhanced the accuracy and amount of rig data gathered, which can then be used in conjunction with operational procedures and torque and drag software to accurately plan and execute completions operations in the wellbore. Using data acquisition software, a constant stream of data was collected in one-second intervals in over two dozen wells. This system has the ability to measure both rotary speed and rotary torque, which are critical parameters when drilling out frac plugs. By removing these assumptions in the post-job analysis over a number of wells, a range of friction factors have been established for the Appalachian Basin in the Utica and Marcellus plays. The authors will present field data from two wells as representative case studies, along with the range of predictive friction factors established from 13 wells for the particular completions operations evaluated in the Permian and Appalachia plays. It is the goal of the authors to disseminate technical information on the methodology and practice of modeling wells post-job, calibrating friction factors, and establishing predictive ranges for successful use in future projects.


2018 ◽  
Vol 935 (5) ◽  
pp. 54-63
Author(s):  
A.A. Maiorov ◽  
A.V. Materuhin ◽  
I.N. Kondaurov

Geoinformation technologies are now becoming “end-to-end” technologies of the new digital economy. There is a need for solutions for efficient processing of spatial and spatio-temporal data that could be applied in various sectors of this new economy. Such solutions are necessary, for example, for cyberphysical systems. Essential components of cyberphysical systems are high-performance and easy-scalable data acquisition systems based on smart geosensor networks. This article discusses the problem of choosing a software environment for this kind of systems, provides a review and a comparative analysis of various open source software environments designed for large spatial data and spatial-temporal data streams processing in computer clusters. It is shown that the software framework STARK can be used to process spatial-temporal data streams in spatial-temporal data streams. An extension of the STARK class system based on the type system for spatial-temporal data streams developed by one of the authors of this article is proposed. The models and data representations obtained as a result of the proposed expansion can be used not only for processing spatial-temporal data streams in data acquisition systems based on smart geosensor networks, but also for processing spatial-temporal data streams in various purposes geoinformation systems that use processing data in computer clusters.


Author(s):  
Tianxing Wang ◽  
Junfeng Yang ◽  
Hongchao Wang ◽  
Hongwei Yu ◽  
Zhengyang Sun ◽  
...  

2012 ◽  
Vol 87 (12) ◽  
pp. 2178-2181 ◽  
Author(s):  
Miguel Correia ◽  
Jorge Sousa ◽  
Álvaro Combo ◽  
António P. Rodrigues ◽  
Bernardo B. Carvalho ◽  
...  

2010 ◽  
Vol 25 (10) ◽  
pp. 749-766
Author(s):  
VIVIAN O'DELL

The CMS Trigger and Data Acquisition Systems have been installed and commissioned and are awaiting data at the Large Hadron Collider. In this article, we describe what factors drove the design and architecture of the systems.


Sign in / Sign up

Export Citation Format

Share Document