Making seismic monitoring work in a complex desert environment — 4D processing

2019 ◽  
Vol 38 (8) ◽  
pp. 637-645 ◽  
Author(s):  
Robert Smith ◽  
Emad Hemyari ◽  
Andrey Bakulin ◽  
Abdullah Alramadhan
Keyword(s):  
Survey Design ◽  
Signal To Noise Ratio ◽  
Time Lapse ◽  
Seismic Monitoring ◽  
Carbonate Reservoir ◽  
Acquisition System ◽  
Desert Environment ◽  
Near Surface ◽  
Different Seasons ◽  
Processing Techniques

Seismic monitoring of an onshore carbonate reservoir in a desert environment has been achieved for the first time. Optimizing data repeatability was key to detecting the weak 4D (time-lapse) signal resulting from a fluid-injection program, which was achieved through a combination of specialized survey design, careful acquisition, and dedicated 4D processing. The hybrid acquisition system utilized buried geophones, which significantly reduced 4D noise caused by variability in the near-surface environment. Despite the extensive acquisition efforts, time-lapse processing is an essential component of achieving highly repeatable data. A fit-for-purpose workflow was developed to reduce the remaining 4D noise using a combination of parallel and simultaneous processing. Processing steps leading to the largest improvement in reflection signal-to-noise ratio, such as noise attenuation, amplitude balancing, and supergrouping, produced the largest reduction in 4D noise. Outstanding final migrated data repeatability has been achieved, comparable to levels reported for the more favorable permanent marine systems. However, the need to use surface sources results in a seasonal imprint on data repeatability, which hinders the interpretation of surveys acquired during different seasons. In the absence of a fully buried acquisition system, advanced processing techniques such as surface-consistent matching filters may be required to resolve these variations.

Comprehensive seismic monitoring of an onshore carbonate reservoir: a case study from a desert environment

2020 ◽  
pp. 581-603
Author(s):  
Robert Smith ◽  
Andrey Bakulin ◽  
Michael Jervis ◽  
Abdullah Alramadhan
Keyword(s):  
Seismic Monitoring ◽  
Carbonate Reservoir ◽  
Desert Environment

scholarly journals Exploiting the airwave for time-lapse reservoir monitoring with CSEM on land

Geophysics ◽  
2011 ◽  
Vol 76 (3) ◽  
pp. A15-A19 ◽  
Author(s):  
Marwan Wirianto ◽  
Wim A. Mulder ◽  
Evert C. Slob
Keyword(s):  
Signal To Noise Ratio ◽  
Time Lapse ◽  
Delta Function ◽  
Skin Depth ◽  
Function Type ◽  
Heterogeneous Model ◽  
Near Surface ◽  
Hydrocarbon Reservoir ◽  
The Earth ◽  
Reservoir Monitoring

In the application of controlled source electromagnetics for reservoir monitoring on land, repeatability errors in the source will mask the time-lapse signal due to hydrocarbon production when recording surface data close to the source. We demonstrate that at larger distances, the airwave will still provide sufficient illumination of the target. The primary airwave diffuses downward into the earth and then is scattered back to the surface. The time-lapse difference of its recorded signal reveals the outline on the surface of the resistivity changes in a hydrocarbon reservoir under production. However, repeatability errors in the primary airwave can destroy the signal-to-noise ratio of the time-lapse data. We present a simple and effective method to remove the primary airwave from the data, which we call partial airwave removal. For a homogeneous half space and a delta-function type of source, the surface expression of the airwave does not depend on frequency. For this reason, the primary airwave can be subtracted from the data using recordings at two frequencies, one low enough with a skin depth of the order of the reservoir depth that is sensitive to the reservoir, the other high enough to only sense the near surface. The method does not affect secondary airwave components created by signals that have propagated through the earth and returned to the surface. We show that the method provides a direct indicator of production-related time-lapse changes in the reservoir. We illustrate this for several models, including a general 3D heterogeneous model and one with strong surface topography, for situations where survey repeatability errors are large.

Making seismic monitoring work in a desert environment with complex near surface

2013 ◽  
Author(s):  
Andrey Bakulin ◽  
Mike Jervis ◽  
Roy Burnstad ◽  
Robert Smith
Keyword(s):  
Seismic Monitoring ◽  
Desert Environment ◽  
Near Surface

DAS/SOV: Rotary seismic sources with fiber-optic sensing facilitates autonomous permanent reservoir monitoring

Geophysics ◽  
2021 ◽  
pp. 1-42
Author(s):  
Julia Correa ◽  
Roman Isaenkov ◽  
Sinem Yavuz ◽  
Alexey Yurikov ◽  
Konstantin Tertyshnikov ◽  
...  
Keyword(s):  
Fiber Optics ◽  
Signal To Noise Ratio ◽  
Time Lapse ◽  
Seismic Monitoring ◽  
Seismic Sources ◽  
Autonomous Operation ◽  
Periodic Data ◽  
Source Signal ◽  
Receiver Arrays ◽  
The Cost

With new developments of fiber-optics sensing and rotary sources, continuous active seismic monitoring for onshore applications has now the opportunity to be fully realized and applied to enhance utilization and resource extraction from the subsurface. To date, conventional seismic monitoring deployments consist primarily of receiver arrays, either fixed or not, with periodic data acquisition campaigns using temporarily deployed sources, resulting in time-lapse data with poor temporal resolution. Only a few niche efforts have demonstrated continuous acquisition using fixed source-receiver networks. Herein, we present initial results of a network of fixed rotary seismic sources, referred to as surface orbital vibrators (SOVs), coupled with a permanent distributed acoustic sensing (DAS) network at the CO2CRC Otway Field Site. While rotary seismic sources are not new, our development of the SOV focused on simplifying the cost and complexity of the source hardware while delivering broad frequency spectrum of the source signal. The upgraded hardware is aligned with a robust methodology for autonomous operation and data processing. At the Otway Site we deployed SOVs at nine locations, monitoring seismic response in seven DAS instrumented wells. Baseline operation of the DAS/SOV sensor array and source system demonstrates its capability with near offsets attaining a signal-to-noise ratio approaching 100 dB with an NRMS of 10%. Furthermore, analyses of travel-time repeatability indicate that the DAS/SOV system can deliver time resolution of +/- 500 µs.

Time-lapse seismic performance of a sparse permanent array: Experience from the Aquistore CO2 storage site

Geophysics ◽  
2015 ◽  
Vol 80 (2) ◽  
pp. WA35-WA48 ◽  
Author(s):  
Don J. White ◽  
Lisa A. N. Roach ◽  
Brian Roberts
Keyword(s):  
Signal To Noise Ratio ◽  
Co2 Storage ◽  
Time Lapse ◽  
Seismic Monitoring ◽  
Storage Site ◽  
Raw Data ◽  
Seismic Surveys ◽  
Monitoring Effort ◽  
Overall Performance ◽  
4D Seismic

A sparse areal permanent array of buried geophones was deployed at the Aquistore [Formula: see text] storage site in Saskatchewan, Canada. The purpose of this array is to facilitate 4D seismic monitoring of [Formula: see text] that is to be injected to the deep subsurface. Use of a sparse buried array is designed to improve the repeatability of time-lapse data and to economize the monitoring effort. Prior to the start of [Formula: see text] injection, two 3D dynamite seismic surveys were acquired in March 2012 and May 2013 using the permanent array. The objective of acquiring these data was to allow an assessment of the data repeatability and overall performance of the permanent array. A comparison of the raw data from these surveys and with a conventional high-resolution 3D vibroseis survey demonstrated that (1) the signal-to-noise ratio for the buried geophones was increased by 6–7 dB relative to surface-deployed geophones and by an additional 20 dB for dynamite relative to a vibroseis source, (2) the use of buried sensors and sources at this site did not appear to be significantly degraded by the effects of ghosting, (3) repeatability for the permanent array data was excellent with a mean normalized root-mean-square (nrms) value of 57% for the raw baseline-monitor difference, (4) the variance of nrms values was higher for shot gathers (18%) compared with receiver gathers (7%), and (5) the raw data repeatability was a factor of three improved over that of comparable surface-geophone data acquired at a nearby location. The use of a sparse buried permanent array at the Aquistore site has demonstrably achieved a reduction in ambient noise levels and overall enhanced data repeatability, both of which are keys to successful 4D seismic monitoring.

scholarly journals Near-surface real-time seismic imaging using parsimonious interferometry

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Sherif M. Hanafy ◽  
Hussein Hoteit ◽  
Jing Li ◽  
Gerard T. Schuster
Keyword(s):  
Fluid Flow ◽  
Real Time ◽  
Temporal Resolution ◽  
Seismic Imaging ◽  
Time Lapse ◽  
Rock Properties ◽  
Recording Time ◽  
Near Surface ◽  
Arrival Times ◽  
Order Of Magnitude

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.

scholarly journals Time-lapse imaging of CO2 migration within near-surface sediments during a controlled sub-seabed release experiment

2021 ◽  
Vol 109 ◽  
pp. 103363
Author(s):  
Ben Roche ◽  
Jonathan M. Bull ◽  
Hector Marin-Moreno ◽  
Timothy G. Leighton ◽  
Ismael H. Falcon-Suarez ◽  
...  
Keyword(s):  
Surface Sediments ◽  
Time Lapse ◽  
Near Surface ◽  
Release Experiment ◽  
Time Lapse Imaging

scholarly journals Quaternion Processing Techniques for Color Synthesized NDT Thermography

2021 ◽  
Vol 11 (2) ◽  
pp. 790
Author(s):  
Pablo Venegas ◽  
Rubén Usamentiaga ◽  
Juan Perán ◽  
Idurre Sáez de Ocáriz
Keyword(s):  
Signal To Noise Ratio ◽  
High Capacity ◽  
Synthetic Data ◽  
Relevant Information ◽  
Color Images ◽  
Destructive Testing ◽  
Application Procedure ◽  
Definition Of ◽  
Characterization Procedure ◽  
Processing Techniques

Infrared thermography is a widely used technology that has been successfully applied to many and varied applications. These applications include the use as a non-destructive testing tool to assess the integrity state of materials. The current level of development of this application is high and its effectiveness is widely verified. There are application protocols and methodologies that have demonstrated a high capacity to extract relevant information from the captured thermal signals and guarantee the detection of anomalies in the inspected materials. However, there is still room for improvement in certain aspects, such as the increase of the detection capacity and the definition of a detailed characterization procedure of indications, that must be investigated further to reduce uncertainties and optimize this technology. In this work, an innovative thermographic data analysis methodology is proposed that extracts a greater amount of information from the recorded sequences by applying advanced processing techniques to the results. The extracted information is synthesized into three channels that may be represented through real color images and processed by quaternion algebra techniques to improve the detection level and facilitate the classification of defects. To validate the proposed methodology, synthetic data and actual experimental sequences have been analyzed. Seven different definitions of signal-to-noise ratio (SNR) have been used to assess the increment in the detection capacity, and a generalized application procedure has been proposed to extend their use to color images. The results verify the capacity of this methodology, showing significant increments in the SNR compared to conventional processing techniques in thermographic NDT.

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