Microseismic monitoring field test using surface, shallow grid, and downhole arrays

Drew, Julian; Primiero, P.; Brook, Keith; Raymer, D.; Probert, T.; Kim, Ahyi; Leslie, David

doi:10.1190/segam2012-0910.1

Cited by 9 publications

(4 citation statements)

References 1 publication

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“…This project will solely focus on the events arising from well 1H and recorded by the deep monitoring well and the surface line arrays. (Drew et al, 2012). Right: cross section sketch of the survey design for treatment well 1H.…”

Section: -2 Survey Layoutmentioning

confidence: 99%

“…Previous research regarding microseismic monitoring mainly focussed on signal and noise comparison between downhole, shallow grid and surface receiver arrays (Peyret et al, 2012;Drew et al, 2012;Schilke, 2013), the application of detection and localisation algorithms for microseismic events (Drew et al, 2005;Bradford et al, 2013;Raymer et al, 2013) and processing techniques to improve the relatively low SNR of surface data (Probert et al, 2013;Raymer et al, 2013;).…”

Section: Introductionmentioning

confidence: 99%

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Factors Influencing the Surface Expressions of Perforation Shots

Renterghem¹,

Probert²,

Bradford³

et al. 2015

Proceedings

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The perforation of the borehole casing and cement is the final stage in any well completion, before hydraulic fracturing, in order to establish a connection with the reservoir. The generated seismic impression characteristics of this crucial step have always been neglected to date and are the topic of this thesis. A downhole and surface hydraulic fracturing monitoring dataset from the Fayetteville Shale has been analysed to develop a better understanding of the seismic perforation expressions and to identify influencing reservoir properties. This requires a combination of data processing and forward modelling. The perforation shots typically give rise to multiple P-wave and S-wave arrivals. In order to match the observed arrivals with the modelled ones, two crucial geological parameters need to be included into the well log based velocity model: an apparently negligible 1.6 • subsurface dip and a strong anisotropy (< 50%) in the Fayetteville Shale. Of equal importance are shot generated waves travelling through the treatment well, also known as tube waves, giving rise to secondary seismic events. These are characterised by low frequency waveforms, which appear to be favourably transported through the borehole and converted into body waves. Hence, the arrivals related to source, propagation, and treatment operation effects become interlinked and need very careful separation and interpretation.

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Section: -2 Survey Layoutmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Factors Influencing the Surface Expressions of Perforation Shots

Renterghem¹,

Probert²,

Bradford³

et al. 2015

Proceedings

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show abstract

“…Downhole array is one of the common observatory systems for microseismic monitoring. It can provide higher quality data than surface/subsurface arrays due to its proximity to the fractured zone (Maxwell et al, 2010(Maxwell et al, , 2012Drew et al, 2012;Meng et al, 2018). For downhole microseismic monitoring, the determination of microseismic event back-azimuth is an important step in the data processing (Maxwell, 2014;Akram, 2020), and the accuracy of event back-azimuth has a significant impact on subsequent source location and fracture interpretation (Cipolla et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

Receiver orientation and event back-azimuth estimation for downhole microseismic monitoring using a probabilistic method based on P-wave polarization

Huang

Tan

et al. 2023

Front. Earth Sci.

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Microseismic event back-azimuth is an indispensable parameter for source localization in downhole microseismic monitoring, and the accurate orientation of horizontal components of downhole seismic receivers is vital for reliably determining the event back-azimuth. Variation in the monitoring data quality may jeopardize the accuracy of receiver orientation which will further affect the event back-azimuth estimation. To mitigate this issue, we proposed a new probabilistic method based on P-wave polarization analysis for receiver orientation and event back-azimuth estimation. The algorithm constructs the von Mises distribution function using the polarization angle and corresponding rectilinearity of the P-wave, then determines the target angle using the maximum of the probability function. The receiver having the highest rectilinearity from the active-source event is used to quantify a reliable absolute orientation angle, and the relative orientation angles are calculated by the probability distributions based on the measurement angle differences and the associated averages of rectilinearity from all events. After receiver orientation, the P-wave polarization angles with different rectilinearity values are applied to construct the probability distribution functions to estimate the event back-azimuths. By using high-quality events and multi-receiver recordings, our methodology can greatly reduce the unintentional error in receiver orientation and increase event back-azimuth accuracy. We investigate the feasibility and reliability of the proposed method using both synthetic and field data. The synthetic data results demonstrate that, compared to the conventional methods, the proposed method can minimize the variance of the receiver orientation angle and back-azimuth estimation. The weighted standard deviation analysis demonstrates that the proposed method can reduce the orientation error and improve the event back-azimuth accuracy in the field dataset.

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“…In addition to ambient and urban noise in many oil and gas producing environments there is also production-induced noise resulting from fluid extraction and injection processes. For hydraulic fracture monitoring pumping noise is pervalent, where increased noise levels are observed at stations closer to treatment wells [e.g., Drew et al, 2012;Schilke et al, 2014] broadly above the expected induced seismicity. It should be noted, however, that ambient noise interferometry on passive seismic data has been used increasingly to image subsurface velocity distributions [e.g., Draganov et al, 2004] and recently multiples are being used to improve event location algorithms [e.g., Belayouni et al, 2015].…”

Section: Introductionmentioning

confidence: 99%

Analysis and models of pre-injection surface seismic array noise recorded at the Aquistore carbon storage site

Birnie

Chambers²,

Angus

et al. 2016

Geophys. J. Int.

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Noise is a persistent feature in seismic data and so poses challenges in extracting increased accuracy in seismic images and physical interpretation of the subsurface. In this paper, we analyse passive seismic data from the Aquistore carbon capture and storage pilot project permanent seismic array to characterise, classify and model seismic noise. We perform noise analysis for a three month subset of passive seismic data from the array and provide conclusive evidence that the noise field is not white, stationary, or Gaussian;characteristics commonly yet erroneously assumed in most conventional noise models. We introduce a novel noise modelling method that provides a significantly more accurate characterisation of real seismic noise compared to conventional methods, which is quantified using the Mann-Whitney-White statistical test. This method is based on a statistical covariance modelling approach created through the modelling of individual noise signals. The identification of individual noise signals, broadly classified as stationary, pseudo-stationary and non-stationary, provides a basis on which to build an appropriate spatial and temporal noise field model. Furthermore, we have developed a workflow to incorporate realistic noise models within synthetic seismic datasets providing an opportunity to test and analyse detection and imaging algorithms under realistic noise conditions.

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Microseismic monitoring field test using surface, shallow grid, and downhole arrays

Cited by 9 publications

References 1 publication

Factors Influencing the Surface Expressions of Perforation Shots

Factors Influencing the Surface Expressions of Perforation Shots

Receiver orientation and event back-azimuth estimation for downhole microseismic monitoring using a probabilistic method based on P-wave polarization

Analysis and models of pre-injection surface seismic array noise recorded at the Aquistore carbon storage site

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