The Potential Role of Passive Seismic Monitoring for Real-Time 4D Reservoir Characterization

2005 ◽  
Vol 8 (01) ◽  
pp. 70-76 ◽  
Author(s):  
S.C. Maxwell ◽  
T.I. Urbancic

Summary This paper details the application of passive seismic monitoring to image reservoir fracturing and deformation from the stage of an initial wellcompletion to final field production. Instrumented oil fields with seismic arrays either permanently installed or temporarily deployed on wireline offer the possibility of imaging production activities in a real-time sense that complements other seismic-reflection and engineering measurements. During the well-completion stage of development, real-time microseismic imaging offers the possibility of monitoring well stimulation. Fracture images may be used to optimize the fracture design and the net present value (NPV) of well production, as well as understand fracture complexity and the associated well-drainage pattern to target future well placement. During production stages, time-lapse microseismic imaging may be used for image deformation associated with fracturing or fracture reactivation from pressure or stress changes, strains in the overburden in fields with casing-deformation problems, and image fronts associated with secondary recovery. In this paper, several case studies are used to illustrate various potential applications, along with discussion of the potential limitations. The reservoir conditions necessary for the successful application of the technology are presented along with a potential method to quantify the technical feasibility at a particular site. Introduction With the current industry trend toward instrumented oil fields and smart-well completions, the permanent deployment of geophones or other acoustic sensors to complement standard engineering gauges is being promoted as a way to map reservoir dynamics. The biggest push is from active time-lapse seismic, although the deployment of permanent seismic instrumentation is also potentially an ideal route to monitor passive seismicity. Passive monitoring of acoustic emissions, or small-magnitude microearthquakes (microseismicity)associated with stress changes in and around the reservoir, can also be used to image the reservoir dynamics. Passive monitoring has the benefit of more fully using the seismic sensors to monitor during periods between conventional seismic surveys, directly imaging fracturing and deformation, and offers complementary information to both active time-lapse images and engineering measurements. Microseismic events, related to either induced movements on pre-existing structures or the creation of new fractures, capture deformations as the rock mass reacts to stresses and strains associated with pressure changes in the reservoir. The microseismicity can be used to localize the fracturing or to deduce geomechanical details of the deformation. Since the Rangely experiment in the late 1960s,1 a number of passive seismic experiments have been pursued in the petroleum industry with varying degrees of success.2–5 Recently, an umber of independent operators have successfully implemented passive seismic studies to address specific issues. The majority of these studies are under the umbrella of hydraulic fracturing,2,3 where the microseismicity is used to map the fracture growth directly during well stimulations. However, a number of other studies have been used to image deformations associated with primary production,4 secondary recovery,4 or waste-injection operations.5 In the vast majority of these cases, an array of seismic sensors is deployed by wireline to monitor for a specific period. This requires finding a well "close to the action" to facilitate detection of these small passive signals without impacting production. Permanent sensor deployment in an instrumented oil field circumvents the chronic problem of well availability. In numerous fields, microseismicity is continually occurring, and if the instrumentation were in place to record the data properly, additional information on the reservoir performance could be gained. As an aside, it is worth considering how much of the "noise" recorded in conventional seismics may be actually valuable microseismic data. The key will be to design the seismic arrays properly to cover both conventional active seismics (e.g., reflection and tomography) and specific issues associated with passive recording. This paper will outline a viewpoint of the potential applications and technical issues associated with passive seismic monitoring. Because passive seismics is probably best viewed as being in its infancy in the petroleum industry, it is worth standing back and considering applications in other industries in which the technology is more mature. In mining, real-time micro seismic data are used by supervisors to decide if it is safe to send miners underground.6 Microseismic data are also crucial in a number of other rock-engineering applications, such as excavation stability in nuclear-wasterepositories,7 geotechnical stability,8 and performance of geothermal reservoirs.9 Permanent instrumentation in oil fields also should allow the maturity of the technology to help solve certain geomechanical problems in the petroleum industry. This article generally will focus on borehole deployments because passive monitoring will most likely involve borehole arrays to keep the instrumentation close to the action and maximize sensitivity. In some special cases, where induced seismic activity can be detected at surface, permanent surface arrays could be used in a context similar to the picture painted in this paper. However, for the most part, the following discussion will focus on borehole arrays.

2014 ◽  
Vol 25 (4) ◽  
pp. 279-287 ◽  
Author(s):  
Stefan Hey ◽  
Panagiota Anastasopoulou ◽  
André Bideaux ◽  
Wilhelm Stork

Ambulatory assessment of emotional states as well as psychophysiological, cognitive and behavioral reactions constitutes an approach, which is increasingly being used in psychological research. Due to new developments in the field of information and communication technologies and an improved application of mobile physiological sensors, various new systems have been introduced. Methods of experience sampling allow to assess dynamic changes of subjective evaluations in real time and new sensor technologies permit a measurement of physiological responses. In addition, new technologies facilitate the interactive assessment of subjective, physiological, and behavioral data in real-time. Here, we describe these recent developments from the perspective of engineering science and discuss potential applications in the field of neuropsychology.


2019 ◽  
Author(s):  
Bettina Goertz-Allmann ◽  
D. Kühn ◽  
K. Iranpour ◽  
M. Jordan ◽  
Benjamin Udo Emmel ◽  
...  

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Sherif M. Hanafy ◽  
Hussein Hoteit ◽  
Jing Li ◽  
Gerard T. Schuster

AbstractResults are presented for real-time seismic imaging of subsurface fluid flow by parsimonious refraction and surface-wave interferometry. Each subsurface velocity image inverted from time-lapse seismic data only requires several minutes of recording time, which is less than the time-scale of the fluid-induced changes in the rock properties. In this sense this is real-time imaging. The images are P-velocity tomograms inverted from the first-arrival times and the S-velocity tomograms inverted from dispersion curves. Compared to conventional seismic imaging, parsimonious interferometry reduces the recording time and increases the temporal resolution of time-lapse seismic images by more than an order-of-magnitude. In our seismic experiment, we recorded 90 sparse data sets over 4.5 h while injecting 12-tons of water into a sand dune. Results show that the percolation of water is mostly along layered boundaries down to a depth of a few meters, which is consistent with our 3D computational fluid flow simulations and laboratory experiments. The significance of parsimonious interferometry is that it provides more than an order-of-magnitude increase of temporal resolution in time-lapse seismic imaging. We believe that real-time seismic imaging will have important applications for non-destructive characterization in environmental, biomedical, and subsurface imaging.


2021 ◽  
Vol 11 (7) ◽  
pp. 3122
Author(s):  
Srujana Neelam ◽  
Audrey Lee ◽  
Michael A. Lane ◽  
Ceasar Udave ◽  
Howard G. Levine ◽  
...  

Since opportunities for spaceflight experiments are scarce, ground-based microgravity simulation devices (MSDs) offer accessible and economical alternatives for gravitational biology studies. Among the MSDs, the random positioning machine (RPM) provides simulated microgravity conditions on the ground by randomizing rotating biological samples in two axes to distribute the Earth’s gravity vector in all directions over time. Real-time microscopy and image acquisition during microgravity simulation are of particular interest to enable the study of how basic cell functions, such as division, migration, and proliferation, progress under altered gravity conditions. However, these capabilities have been difficult to implement due to the constantly moving frames of the RPM as well as mechanical noise. Therefore, we developed an image acquisition module that can be mounted on an RPM to capture live images over time while the specimen is in the simulated microgravity (SMG) environment. This module integrates a digital microscope with a magnification range of 20× to 700×, a high-speed data transmission adaptor for the wireless streaming of time-lapse images, and a backlight illuminator to view the sample under brightfield and darkfield modes. With this module, we successfully demonstrated the real-time imaging of human cells cultured on an RPM in brightfield, lasting up to 80 h, and also visualized them in green fluorescent channel. This module was successful in monitoring cell morphology and in quantifying the rate of cell division, cell migration, and wound healing in SMG. It can be easily modified to study the response of other biological specimens to SMG.


2021 ◽  
Author(s):  
Ryan Daher ◽  
Nesma Aldash

Abstract With the global push towards Industry 4.0, a number of leading companies and organizations have invested heavily in Industrial Internet of Things (IIOT's) and acquired a massive amount of data. But data without proper analysis that converts it into actionable insights is just more information. With the advancement of Data analytics, machine learning, artificial intelligence, numerous methods can be used to better extract value out of the amassed data from various IIOTs and leverage the analysis to better make decisions impacting efficiency, productivity, optimization and safety. This paper focuses on two case studies- one from upstream and one from downstream using RTLS (Real Time Location Services). Two types of challenges were present: the first one being the identification of the location of all personnel on site in case of emergency and ensuring that all have mustered in a timely fashion hence reducing the time to muster and lessening the risks of Leaving someone behind. The second challenge being the identification of personnel and various contractors, the time they entered in productive or nonproductive areas and time it took to complete various tasks within their crafts while on the job hence accounting for efficiency, productivity and cost reduction. In both case studies, advanced analytics were used, and data collection issues were encountered highlighting the need for further and seamless integration between data, analytics and intelligence is needed. Achievements from both cases were visible increase in productivity and efficiency along with the heightened safety awareness hence lowering the overall risk and liability of the operation. Novel/Additive Information: The results presented from both studies have highlighted other potential applications of the IIOT and its related analytics. Pertinent to COVID-19, new application of such approach was tested in contact tracing identifying workers who could have tested positive and tracing back to personnel that have been in close proximity and contact therefore reducing the spread of COVID. Other application of the IIOT and its related analytics has also been tested in crane, forklift and heavy machinery proximity alert reducing the risk of accidents.


Sign in / Sign up

Export Citation Format

Share Document