Estimates of individual fracture compliances along boreholes from full‐waveform sonic log data

Author(s):  
Nicolás D. Barbosa ◽  
Andrew Greenwood ◽  
Eva Caspari ◽  
Nathan Dutler ◽  
Klaus Holliger
Keyword(s):  
Log Data ◽  
2019 ◽  
Vol 124 (3) ◽  
pp. 2738-2761 ◽  
Author(s):  
Nicolás D. Barbosa ◽  
Eva Caspari ◽  
J. Germán Rubino ◽  
Andrew Greenwood ◽  
Ludovic Baron ◽  
...  

2020 ◽  
Author(s):  
Nicolás D. Barbosa ◽  
Eva Caspari ◽  
Andrew Greenwood ◽  
Klaus Holliger

2021 ◽  
Author(s):  
Zhenya Zhou ◽  
Eva Caspari ◽  
Nicolás D. Barbosa ◽  
Andrew Greenwood ◽  
Klaus Holliger

<p>Fractures, which are ubiquitous in the Earth’s upper crust, have significant impacts on a wide range of human activities, and, hence, their adequate characterization is of wide interest and importance. Seismic methods have significant potential for effectively addressing this objective. When a seismic wave propagates across a fluid-filled fracture, its amplitude is diminished and its travel time is increased. Based on the linear slip theory, the associated amplitude decays and phase delays<strong> </strong>can be used to estimate the mechanical compliance of fractures.<strong> </strong>Full-waveform sonic (FWS) log data are particularly well-suited for this purpose. While the amplitudes of FWS data acquired during standard continuous logging runs (tool being moved uphole at a constant logging speed) can be somewhat unstable, the associated first-arrival travel times are generally quite robust. In this work, we exploit the relation between the time delay that seismic waves experience across fractures and relate them to the associated compliances. Specifically, we estimate fracture compliance from the differences in group time delay of the refracted P-wave between fractured and non-fractured sections along a borehole. Numerical simulations indicate that the proposed method provides reliable compliance estimates not only for individual fractures, but also for sets of multiple discrete fractures. This finding is corroborated by applying our approach to FWS log data acquired in the course of standard logging runs in the Bedretto Underground Laboratory (www.bedrettolab.ethz.ch). Our estimates are comparable to previously inferred compliance values in a closely comparable geological environment (Grimsel test site, www.grimsel.com). The latter were inferred under rather ideal conditions, involving the quasi-static acquisition of the FWS data as well as the combination of amplitude and travel time information for their interpretation. An interesting and important open question, which we plan to address in the following, concerns the influence of the heterogeneity of the host rock embedding the fractures on compliance estimation in general and on the proposed method in particular.</p>


2021 ◽  
pp. 1-15
Author(s):  
Amit Govil ◽  
Harald Nevøy ◽  
Lars Hovda ◽  
Guillermo A. Obando Palacio ◽  
Geir Kjeldaas

Summary As part of plug and abandonment (P&A) operations, several acceptance criteria need to be considered by operators to qualify barrier elements. In casing annuli, highly bonded material is occasionally found far above the theoretical top of cement. This paper aims to describe how the highly bonded material can be identified using a combination of ultrasonic logging data, validated with measurements in laboratory experiments using reference cells and how this, in combination with data from the well construction records, can contribute to lowering the costly toll of P&A operations. Ultrasonic and sonic log data were acquired in several wells to assess the bond quality behind multiple casing sizes in an abandonment campaign. Data obtained from pulse-echo and flexural sensors were interactively analyzed with a crossplotting technique to distinguish gas, liquid, barite, cement, and formation in the annular space. Within the methodology used, historical data on each well were considered as an integral part of the analysis. During the original well construction, either water-based mud (WBM) or synthetic oil-based mud (OBM) was used for drilling and cementing operations, and some formation intervals consistently showed high bonding signatures under specific conditions, giving clear evidence of formation creep. Log data from multiple wells confirm that formation behavior is influenced by the type of mud used during well construction. The log data provided information of annulus material with a detailed map of the axial and azimuthal variations of the annulus contents. In some cases, log response showed a clear indication of formation creep, evidenced by a high bond quality around the production casing where cement cannot be present. Based on observations from multiple fields in the Norwegian continental shelf, a crossplot workflow has been designed to distinguish formation from cement as the potential barrier element. NORSOK Standard D-010 (2013) has initial verification acceptance criteria both for annulus cement and creeping formation as a well barrier element, both involving bond logs; however, in the case of creeping formation, it is more stringent stating that “two independent logging measurements/tools shall be applied.” This paper aims to demonstrate how this can be done with confidence using ultrasonic and sonic log data, validated against reference barrier cells (Govil et al. 2020). Logging responses like those gathered during full-scale experiments of reference barrier cells with known defects were observed in multiple wells in the field. Understanding the phenomenon of formation creep and its associated casing bond signature could have a massive impact on P&A operations. With a successful qualification of formation as an annulus barrier, significant cost and time savings can be achieved.


Author(s):  
Tomio Inazaki ◽  
Toshiyuki Kurahashi ◽  
Shiro Watanabe
Keyword(s):  
Log Data ◽  

2012 ◽  
Vol 64 (12) ◽  
pp. 130-132
Author(s):  
Dennis Denney
Keyword(s):  
Log Data ◽  

2021 ◽  
Author(s):  
Saeed Aftab ◽  
Rasoul Hamidzadeh Moghadam

Abstract Well logging is an essential approach to making geophysical surveys and petrophysical measurements and plays a key role to interpret downhole conditions. But, well logging signals usually contain noise that distorts results and causes ambiguous interpretations. In this paper, the wavelet filter and robust data smoothing algorithms are tested for denoising synthetic sonic log and field sonic log data. Robust data smoothing algorithms include Gaussian, RLOESS (Robust locally estimating scatterplot smoothing), and RLOWESS (Robust locally weighted scatterplot smoothing) methods. Uniform and normal distribution noise applied to synthetic model and results revealed that the wavelet filter performs better than data smoothing algorithms for denoising uniform distribution noise. However, the RLOESS removed uniform noise acceptably. But, for normal distribution noise, the wavelet filter disrupts and data smoothing algorithms, specifically RLOESS attenuated noise perfectly. Due to the noise nature of field sonic log data, wavelet filter completely disrupts, but data smoothing algorithms removed the noise of field data more efficiently, particularly RLOESS. So, we can express that RLOESS is a perfect algorithm for denoising sonic log signals, regardless of noise nature.


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