A low-frequency passive seismic array experiment over an onshore oil field in Abu Dhabi, United Arab Emirates

Abstract

A low-frequency passive seismic experiment using an array of 49 3C broadband seismometers was conducted over an onshore oil field in the emirate of Abu Dhabi in the United Arab Emirates. The aim of the experiment was to understand the characteristics and origins of the microseism (0.15–0.4 Hz) and microtremor (about 1–6 Hz) signals recorded, the latter having been reported as being a hydrocarbon indicator above several reservoirs in the region. The recorded array data were analyzed for their polarization, apparent velocities, and wavefront azimuths using various techniques, including spectral and time-frequency analyses, particle motion, H/V spectral ratios, and high-resolution frequency-wavenumber (f-k) analyses. In the frequency range of 0.15–0.4 Hz, the dominant feature observed consisted of double-frequency microseisms peaks generated by the nonlinear interactions of ocean waves with the shoreline along the coasts of the Arabian Sea and the Arabian Gulf. The f-k analyses confirmed that microtremor events in the frequency range of 2–3 Hz have an azimuth pointing toward a major oil pipeline and oil plant facilities to the west–southwest of the study area, as well as a motorway to the southeast. This would indicate that the microtremor events are probably caused by local sources, including the continuous movement of oil through the pipeline, the noise from oil plant facilities, as well as nearby traffic noise. This interpretation was confirmed by the polarization analysis performed on the data. The data also indicated that no clear correlation exists between the microtremor signal and local meteorological conditions. Although some body waves with an infinite apparent velocity generated by earthquakes were recorded, no other body waves that could have possibly been generated by hydrocarbon reservoirs were observed using the analyses techniques used in this study. Therefore, our results indicated that for the site under investigation, the microseism and the microtremor signals detected could not be related to the presence of hydrocarbon accumulations in the subsurface, but instead they may be attributed to local anthropogenic sources.

High‐Resolution Ambient Noise Imaging of Geothermal Reservoir Using 3C Dense Seismic Nodal Array and Ultra‐Short Observation

“…Following the pioneering work of Campillo and Paul (2003), ambient noise interferometry can be used to estimate an approximate Green's function between two receivers by cross-correlating the ambient seismic wavefield (Bensen et al, 2007;Nakata et al, 2015;Shapiro & Campillo, 2004;Snieder, 2004;Snieder et al, 2009;Wapenaar, 2004). This approach has been applied to characterize multiple scales of earth structure: from the global scale or continental scale deep-structure imaging in seismology (e.g., Lin et al, 2008Lin et al, , 2009Strobbia & Cassiani, 2011;Yang et al, 2007;Yao & van der Hilst, 2009) to local scale exploration (e.g., Ali et al, 2013;Bakulin & Calvert, 2006;Behm et al, 2014Behm et al, , 2019Castellanos et al, 2020;Cheng et al, 2015Cheng et al, , 2016Cheng et al, , 2018Cheng et al, , 2021Draganov et al, 2009;Nakata et al, 2011Nakata et al, , 2016Wapenaar et al, 2008). Ambient noise interferometry is usually performed with surface wave tomography based on multiple-station (tens or more) networks and long-term (months or years) continuous observations (Lin et al, 2008;Martins et al, 2019;Planès et al, 2020).…”

Multi-Scale Seismic Measurements for Site Characterization and CO2 Monitoring in an Enhanced Oil Recovery/Carbon Capture, Utilization, and Sequestration Project, Farnsworth Field, Texas

“…Likewise, the success of the noise attenuation algorithms may suggest that the industrial operations associated with the active oilfield have the potential to substantially interfere with the seismic processing and interpretation. Ali et al [23] also observed potential anthropogenic sources of noise in an oilfield in Saudi Arabia. Currently, several different denoising techniques are available, such as the continuous wavelet transform and the DeepDenoiser, but they suffer from computational cost and the necessity to retrain the models for each site [24][25][26].…”

Improving Surface Wave Retrieval From Traffic Noise by Deconvolution of the Decomposed Wavefield

“…Among the numerous algorithms to achieve Vs images using passive seismic recordings, seismic interferometry refers to a class of methods with which the empirical Green's function between two receiver locations is retrieved by crosscorrelating their recordings. These methods have been extensively studied to extract low frequency surface waves (<1 Hz) to image the deep earth (Campillo & Paul, 2003; Chen et al., 2014; Lobkis & Weaver, 2001; Shapiro & Campillo, 2004; Snieder, 2004) as well as high frequency surface waves to investigate the shallow subsurface(Ali et al., 2013; Dong et al., 2006; Draganov et al., 2013; Halliday et al., 2007; Nakata et al., 2011; Pan et al., 2016; Xue et al., 2009). One important advantage of seismic interferometry methods for passive surface wave imaging is that the waveform of surface wave can be estimated, which allows for FWI for the subsurface Vs distribution.…”