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EN
Microseismic (MS) monitoring is a short-term rockburst prediction technique that foretells the source, time and damage scale inside a rock mass during the rock fracturing process; however, due to the complex underground environment and mechanism of rockburst it is always hard to reliably predict the damage scale (severity) of rockburst manually; therefore, this paper introduces machine learning (ML) approach using nonlinear support vector machine (Nonlinear-SVM) to predict the short-term rockburst. Six indicators, cumulative number of events (N), cumulative seismic energy (E), cumulative apparent volume(V), event rate (NR), seismic energy rate (ER) and apparent volume rate (VR), are selected as an input indices for Nonlinear-SVM which is trained and tested with randomly selected 85 and 22 samples of rockburst cases, respectively, collected from different literature. The constructed model was employed to predict the short-term rockburst severity. After data standardisation, cross-validation and hyperparameter optimisation, the prediction accuracy reached 86% for the test sample. The predicted rockburst result truly matches the actual situation with few misclassifcations. Therefore, the proposed method has potential value for the short-term rockburst prediction task.
EN
The monitoring of microseismicity during temporary human activities such as fluid injections for hydrofracturing, hydrothermal stimulations or wastewater disposal is a difficult task. The seismic stations often cannot be installed on hard rock, and at quiet places, noise is strongly increased during the operation itself and the installation of sensors in deep wells is costly and often not feasible. The combination of small-aperture seismic arrays with shallow borehole sensors offers a solution. We tested this monitoring approach at two different sites: (1) accompanying a fracking experiment in sedimentary shale at 4 km depth and (2) above a gas field under depletion. The small-aperture arrays were planned according to theoretical wavenumber studies combined with simulations considering the local noise conditions. We compared array recordings with recordings available from shallow borehole sensors and give examples of detection and location performance. Although the high-frequency noise on the 50-m-deep borehole sensors was smaller compared to the surface noise before the injection experiment, the signals were highly contaminated during injection by the pumping activities. Therefore, a set of three small-aperture arrays at different azimuths was more suited to detect small events, since noise recorded on these arrays is uncorrelated with each other. Further, we developed recommendations for the adaptation of the monitoring concept to other sites experiencing induced seismicity.
PL
W artykule przedstawiono wyniki obliczeń uzyskanych autorskim programem MICROMOD 3D, opracowanym w ramach realizacji programu Blue Gas – projekt GASLUPMIKROS. Otrzymane rezultaty należy traktować jako testowanie ogólności zaproponowanego rozwiązania, szczegółowo opisanego w publikacji [1]. Testowanie prowadzono na modelach teoretycznych, stworzonych na podstawie rzeczywistych danych pozyskanych na jednej z koncesji PGNiG. Komentarz dotyczący wyników dla kolejnych modeli odnosi się raczej do metodyki funkcjonalnej programu, która zapewnia możliwość zastosowania go dla 3 najczęściej realizowanych wersji monitoringu sejsmicznego (powierzchniowego, otworowego oraz odbiorników pogrążonych). Przedstawione rezultaty pozwalają pozytywnie ocenić opracowany program oraz rekomendować jego wykorzystanie w bieżących pracach przemysłowych, zarówno w projektowaniu akwizycji dla mikroszczelinowania hydraulicznego, jak też przy weryfikacji obliczanych parametrów geomechanicznych ośrodka geologicznego. Ponadto wyniki modelowań standardowo stanowią wsparcie dla prac interpretacyjnych sejsmiki.
EN
In the paper the results of calculations obtained by way of the Micromod 3D software, developed as part of the Blue Gas project – GASLUPMIKROS are presented. These results should be treated as general testing of the proposed solution, described in detail in the publication [1]. Testing was conducted on theoretical models, created on the basis of real data, obtained from one of the PGNiG concessions. Comments on the results for the following models refers rather to the methodology of the software functionality, which provides the ability to use the Micromod 3D for the three most frequently performed types of the seismic monitoring: surface sensor network, downhole sensors, and shallow buried array. The results allow to positively evaluate the developed software and recommend its use in the ongoing work in the industry, both in the design of acquisition for hydraulic fracturing as well as the verification of calculated geomechanical parameters of geological medium. Furthermore, the microseismic modeling results provides support for seismic interpretation.
EN
Long Period Long Duration (LPLD) signals are unusual seismic events that can be observed during hydraulic fracturing. These events are very similar in appearance to tectonic tremors sequences, which were first observed in subduction zones. Their nature is not well known. LPLD might be related to the productivity of the reservoir. Different methods of the LPLD events’ detection recorded during hydraulic fracturing are presented. The author applied two methods for LPLD detection – Butterworth filtering and Continuous Wavelet Transform (CWT). Additionally, a new approach to LPLD events detection – instantaneous seismic attributes – was used, common in a classical seismic interpretation but not in microseismic monitoring.
PL
Komunikat przedstawia sposób wykonania badań geofizycznych, mających na celu potwierdzenie efektywności dwunastoetapowego szczelinowania hydraulicznego w otworze horyzontalnym Syczyn-OU2K. Badania objęły pomiary z wykorzystaniem czujników umieszczonych w otworze, powierzchniowych linii geofonowych oraz czujników i sensorów zacementowanych w płytkich otworach. Analiza przeprowadzonych badań wykazała zbieżność wyników otrzymanych z użyciem wszystkich metod, z zastrzeżeniem, że czułość pomiarów powierzchniowych – ze względu na wysoki poziom hałasu, głównie z powierzchni terenu – jest mniejsza niż pomiarów w głębokim otworze.
EN
This memorandum presents the method of performing geophysical research pursued to confirm the effectiveness of 12-stage hydraulic fracturing in the Syczyn-OU2K horizontal borehole. The research included measurements with detectors located in the borehole, surface geophone lines as well as sensors and detectors cemented in shallow boreholes. The analysis of performed research showed the similarities in results obtained by all methods, with the reservation that the sensitivity of surface measurements is lower than those from a deep borehole due to the high noise pollution, mostly from the surface.
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