Single-Phase Production Profiling in Conventional Oil Producers Using Fiber-Optic Surveillance

2021 ◽  
Author(s):  
Peter in ‘t Panhuis ◽  
Lujaina Al Shidhani ◽  
Sultan Al Bahri ◽  
Gijs Hemink

Abstract The objective of this paper is to demonstrate how both Distributed Acoustic Sensing (DAS) and Distributed Temperature Sensing (DTS) data, acquired using a fiber-optic cable installed and cemented behind a 7" production casing, could be used for single-phase production allocation in two conventional oil producers in the South of the Sultanate of Oman. DAS data can be processed, time-averaged, and filtered to specific frequency bands, to identify and monitor the acoustic frequencies that are excited by the flow through the perforation tunnels. It will be shown that under certain assumptions, the flow-induced acoustic amplitudes at the perforations can be calibrated and converted into actual flow rates, which allows for continuous production profiling across all intervals of interest. DTS data, acquired under transient conditions, can also be analyzed using a thermal simulation model, to allocate production to specific perforation intervals, provided an appropriate logging program is followed. DTS is not as good as DAS in capturing dynamic changes to the inflow profile, but does have a deeper depth of investigation and is less sensitive to the geometry of the perforation tunnels or possible flow obstructions in the wellbore. The two technologies are therefore complimentary and are best acquired simultaneously. This is the first case study in the Sultanate of Oman, where both DAS and DTS data sets were successfully acquired and interpreted for single-phase production profiling in a conventional oil producer with perforated casing. Moreover, it was also the first time in Oman that oriented perforation was achieved with full shot density, through a double perforation run with a slight offset in orientation angle between the two runs.

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Mark B. Hausner ◽  
Scott Kobs

Fiber-optic distributed temperature sensing (DTS) makes it possible to observe temperatures on spatial scales as fine as centimeters and at frequencies up to 1 Hz. Over the past decade, fiber-optic DTS instruments have increasingly been employed to monitor environmental temperatures, from oceans to atmospheric monitoring. Because of the nature of environmental deployments, optical fibers deployed for research purposes often encounter step losses in the Raman spectra signal. Whether these phenomena occur due to cable damage or impingements, sharp bends in the deployed cable, or connections and splices, the step losses are usually not adequately addressed by the calibration routines provided by instrument manufacturers and can be overlooked in postprocessing calibration routines as well. Here we provide a method to identify and correct for the effects of step losses in raw Raman spectra data. The utility of the correction is demonstrated with case studies, including synthetic and laboratory data sets.


2021 ◽  
Vol 7 (20) ◽  
pp. eabe7136
Author(s):  
Robert Law ◽  
Poul Christoffersen ◽  
Bryn Hubbard ◽  
Samuel H. Doyle ◽  
Thomas R. Chudley ◽  
...  

Measurements of ice temperature provide crucial constraints on ice viscosity and the thermodynamic processes occurring within a glacier. However, such measurements are presently limited by a small number of relatively coarse-spatial-resolution borehole records, especially for ice sheets. Here, we advance our understanding of glacier thermodynamics with an exceptionally high-vertical-resolution (~0.65 m), distributed-fiber-optic temperature-sensing profile from a 1043-m borehole drilled to the base of Sermeq Kujalleq (Store Glacier), Greenland. We report substantial but isolated strain heating within interglacial-phase ice at 208 to 242 m depth together with strongly heterogeneous ice deformation in glacial-phase ice below 889 m. We also observe a high-strain interface between glacial- and interglacial-phase ice and a 73-m-thick temperate basal layer, interpreted as locally formed and important for the glacier’s fast motion. These findings demonstrate notable spatial heterogeneity, both vertically and at the catchment scale, in the conditions facilitating the fast motion of marine-terminating glaciers in Greenland.


Ground Water ◽  
2012 ◽  
Vol 51 (5) ◽  
pp. 670-678 ◽  
Author(s):  
Matthew W. Becker ◽  
Brian Bauer ◽  
Adam Hutchinson

2021 ◽  
Author(s):  
Abdulaziz Al-Qasim ◽  
Sharidah Alabduh ◽  
Muhannad Alabdullateef ◽  
Mutaz Alsubhi

Abstract Fiber-optic sensing (FOS) technology is gradually becoming a pervasive tool in the monitoring and surveillance toolkit for reservoir engineers. Traditionally, sensing with fiber optic technology in the form of distributed temperature sensing (DTS) or distributed acoustic sensing (DAS), and most recently distributed strain sensing (DSS), distributed flow sensing (DFS) and distributed pressure sensing (DPS) were done with the fiber being permanently clamped either behind the casing or production tubing. Distributed chemical sensing (DCS) is still in the development phase. The emergence of the composite carbon-rod (CCR) system that can be easily deployed in and out of a well, similar to wireline logging, has opened up a vista of possibilities to obtain many FOS measurements in any well without prior fiber-optic installation. Currently, combinations of distributed FOS data are being used for injection management, well integrity monitoring, well stimulation and production performance optimization, thermal recovery management, etc. Is it possible to integrate many of the distributed FOS measurements in the CCR or a hybrid combination with wireline to obtain multiple measurements with one FOS cable? Each one of FOS has its own use to get certain data, or combination of FOS can be used to make a further interpretation. This paper reviews the state of the art of the FOS technology and the gamut of current different applications of FOS data in the oil and gas (upstream) industry. We present some results of traditional FOS measurements for well integrity monitoring, assessing production and injection flow profile, cross flow behind casing, etc. We propose some nontraditional applications of the technology and suggest a few ways through. Which the technology can be deployed for obtaining some key reservoir description and dynamics data for reservoir performance optimization.


2006 ◽  
Vol 326-328 ◽  
pp. 823-826
Author(s):  
Li Li Xin ◽  
Gregory S. Chirikjian

This paper concerns a mechanics of interactions of helical structures in proteins. Helices are the most important secondary structures of proteins and contribute the formation of a more complex 3-D structure, and so the analysis of interactions of helices is quite critical. We examine 1290 protein structures that have 2.0 Å or better resolutions and less than 20 percent of their sequences in common. Interactions between helices are represented by two parameters: the distance and angle. Assuming that helices are slender rigid rods with finite length, we define three different mechanisms of interactions: (1) line-on-line contact; (2) endpoint-to-line contact; and (3) endpointto- endpoint contact. In this paper, interactions for the first case are expressed with the 3-D relative rigid-body motion (position and orientation) and the unique volume element for correctly integrating over rigid-body motions are determined using six parameters. The results are extremely useful for the correct analysis of interactions in terms of distance and angle without the statistical biases inherent in the three data sets.


2012 ◽  
pp. 163-186
Author(s):  
Jirí Krupka ◽  
Miloslava Kašparová ◽  
Pavel Jirava ◽  
Jan Mandys

The chapter presents the problem of quality of life modeling in the Czech Republic based on classification methods. It concerns a comparison of methodological approaches; in the first case the approach of the Institute of Sociology of the Academy of Sciences of the Czech Republic was used, the second case is concerning a project of the civic association Team Initiative for Local Sustainable Development. On the basis of real data sets from the institute and team initiative the authors synthesized and analyzed quality of life classification models. They used decision tree classification algorithms for generating transparent decision rules and compare the classification results of decision tree. The classifier models on the basis of C5.0, CHAID, C&RT and C5.0 boosting algorithms were proposed and analyzed. The designed classification model was created in Clementine.


Author(s):  
Petr Praus

In this chapter the principals and applications of principal component analysis (PCA) applied on hydrological data are presented. Four case studies showed the possibility of PCA to obtain information about wastewater treatment process, drinking water quality in a city network and to find similarities in the data sets of ground water quality results and water-related images. In the first case study, the composition of raw and cleaned wastewater was characterised and its temporal changes were displayed. In the second case study, drinking water samples were divided into clusters in consistency with their sampling localities. In the case study III, the similar samples of ground water were recognised by the calculation of cosine similarity, the Euclidean and Manhattan distances. In the case study IV, 32 water-related images were transformed into a large image matrix whose dimensionality was reduced by PCA. The images were clustered using the PCA scatter plots.


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