Passive Microseismic Data Research Articles

Integrated Active and Passive Seismic Monitoring at the Decatur CCS Project

For holistic seismic monitoring of the progressing CO2 plume within the Mt. Simon sandstone reservoir at the Illinois Basin - Decatur CCS project, we aim to integrate passive microseismic data with complementary surface- and VSP data from active seismic surveys. A detailed microseismic analysis allows for spatial mapping of attenuation Q around the injection area. We identify time periods of possible reservoir changes in between active seismic time-lapse monitors and we can increase the temporal resolution of the 4D signal. In addition, finite-difference FD modeling of microseismic events can help explain the details of the observed waveforms including different phase arrivals for up- and downgoing waves. This, in turn, is essential to improve the depth resolution of microseismic event location and determine whether seismic activity is confined to the injection zone or growing outward. The discrimination of ray paths from FD modelling also allows to select the most relevant waveform phases for 4D time-lapse studies and is an important pre-processing step. In combination with simultaneous tomographic inversion of the velocity- and attenuation structure, it has the potential to maximize the resolution of 4D changes in the medium.

Characterizing the complexity of microseismic signals at slow-moving clay-rich debris slides: the Super-Sauze (southeastern France) and Pechgraben (Upper Austria) case studies

Abstract. Soil and debris slides are prone to rapid and dramatic reactivation. Deformation within the instability is accommodated by sliding, whereby weak seismic energies are released through material deformation. Thus, passive microseismic monitoring provides information that relates to the slope dynamics. In this study, passive microseismic data acquired at Super-Sauze (southeastern France) and Pechgraben (Upper Austria) slow-moving clay-rich debris slides (“clayey landslides”) are investigated. Observations are benchmarked against previous similar case studies to provide a comprehensive and homogenized typology of microseismic signals at clayey landslides. A thorough knowledge of the various microseismic signals generated by slope deformation is crucial for the future development of automatic detection systems to be implemented in landslide early-warning systems. Detected signals range from short-duration (< 2 s) quake-like signals to a wide variety of longer-duration tremor-like radiations (> 2 s – several min). The complexity of seismic velocity structures, the low quantity and low quality of available signal onsets and non-optimal seismic network geometry severely impedes the source location procedure; thus, rendering source processes characterization challenging. Therefore, we constrain sources' locations using the prominent waveform amplitude attenuation pattern characteristic of near-source area (< about 50 m) landslide-induced microseismic events. A local magnitude scale for clayey landslides (ML−LS) is empirically calibrated using calibration shots and hammer blow data. The derived ML−LS returns daily landslide-induced microseismicity rates that positively correlate with higher average daily displacement rates. However, high temporal and spatial resolution analyses of the landslide dynamics and hydrology are required to better decipher the potential relations linking landslide-induced microseismic signals to landslide deformation.

Wigner distribution based phase-only correlation

Identifications of similar seismic events are needed for locating source position and evaluating the subsurface structure from passive micro-seismic data. Phase-only correlation (POC) is used to measure similarity of waveforms and there are three key steps for the implementation: 1). Transform original data into time-frequency domain by shorttime Fourier transform (STFT); 2). Calculate the POC function based on time-frequency data; 3). Estimate the similarity of waveforms by the peak value of POC function. However, the low resolution of STFT limits the performance. To overcome this drawback, we propose an improved POC method by using Wigner distribution to replace STFT and we name it WPOC in this paper. We apply WPOC to both synthetic and field data. The comparison of results obtained by POC and WPOC clearly show that the proposed WPOC is more effective than POC for evaluating similarity of waveforms.

Strategy for automated analysis of passive microseismic data based on S-transform, Otsu’s thresholding, and higher order statistics

Small-magnitude seismic events, either natural or induced microearthquakes, have increasingly been used in exploration seismology with applications ranging from hydrocarbon and geothermal reservoir exploration to high-resolution passive seismic tomography surveys. We developed an automated methodology for processing and analyzing continuously recorded, single-channel seismic data. This method comprised a chi-squared-based statistical test for microseismic event detection and denoising filtering in the S-transform domain based on the Otsu thresholding method. An automatic P-phase picker based on higher order statistics criteria was used. The method was used with data from a surface seismic station. The performance of the method was tested and evaluated on synthetic and real data from a microseismic network used in a high-resolution PST survey and revealed a high level of consistency.

Passive Microseismic Experiments at King Fahd University of Petroleum and Minerals in Saudi Arabia

Passive microseismic research is still a relatively new technology in the oil and gas industry. To date, very little has been explored by Middle Eastern universities and research centers on the use of passive microseismic data for reservoir monitoring and characterization, with the exception of hydraulic fracture monitoring which has recently been established as a commercial service. To fill this gap, I at King Fahd University of Petroleum and Minerals (KFUPM), under the National Science Technology and Innovation Plan of the King Abdulaziz City for Science and Technology (KACST) program, have initiated a pilot experiment to better understand subsurface reservoirs through the use of passive microseismic data. Meanwhile, recent advances in passive seismic research indicate that significant efforts are needed to separate the near-vertically propagating wavefield (possibly crossing a reservoir) from the near-surface noise (particularly in Saudi Arabia, which is very well known for its complex near-surface conditions). Such a separation is a key prerequisite for understanding and characterizing reservoirs. Some researchers suggest that good correlations exist between passive microseismic data and near-surface features (Hanssen and Bussat, 2008) as well as between passive microseismic data and weather, human activities (Ali et al. , 2010), and seasonal changes (Vesnaver et al. , 2003). Consequently, I have deployed an array of three-component passive microseismic recording stations over different geologic conditions on the KFUPM campus to better understand the origin of various near-surface noises and to develop algorithms to remove them. My long-term vision is to develop passive microseismic technology as an additional reliable tool for hydrocarbon exploration in Saudi Arabia. In this article, I present the preliminary results obtained from passive microseismic stations distributed at various locations of interest over the Dammam Dome structure on the KFUPM campus. Over the last decade, a number of workshops and dedicated technical sessions on passive …

A strategy for automated analysis of passive microseismic data to image seismic anisotropy and fracture characteristics

ABSTRACTMonitoring of induced seismicity is gaining importance in a broad range of industrial operations from hydrocarbon reservoirs to mining to geothermal fields. Such passive seismic monitoring mainly aims at identifying fractures, which is of special interest for safety and productivity reasons. By analysing shear‐wave splitting it is possible to determine the anisotropy of the rock, which may be caused by sedimentary layering and/or aligned fractures, which in turn offers insight into the state of stress in the reservoir. We present a workflow strategy for automatic and effective processing of passive microseismic data sets, which are ever increasing in size. The automation provides an objective quality control of the shear‐wave splitting measurements and is based on characteristic differences between the two independent eigenvalue and cross‐correlation splitting techniques. These differences are summarized in a quality index for each measurement, allowing identification of an appropriate quality threshold. Measurements above this threshold are considered to be of good quality and are used in further interpretation. We suggest an automated inversion scheme using rock physics theory to test for best correlation of the data with various combinations of fracture density, its strike and the background anisotropy. This fully automatic workflow is then tested on a synthetic and a real microseismic data set.

Imaging hydraulic fracture zones from surface passive microseismic data

Vladimir A. Kochnev, Ilya V. Goz, Vitaly S. Polyakov, Issa S. Murtayev, Vladimir G. Savin, Boris K. Zommer, and Ilya V. Bryksin provide some Russian examples of passive microseismic applications for imaging hydraulic fracture zones. Most of the current microseismic methods for hydraulic fracture imaging employ multi-level receiver systems deployed on a wireline array in one or more offset wellbores. A high frequency range (over 100 Hz) of receivers is required (Rutledge et al., 2003, Li et al., 1998, Block et al., 1994, Meadows et al., 1994). Locations of microseisms are calculated from the direction of arrived elastic waves and delays of S-waves from corresponding P-waves. To determine the direction of arrival of separate waves is not a trivial task, further complicated by a large numbers of microseismic events (microearthquakes). For robustness, multiple receiver locations are necessary.