Toward Real-time Microseismic Event Detection using the YOLOv3 Algorithm

Real-time microseismic monitoring is essential for understanding fractures associated with underground fluid injection in unconventional reservoirs. However, microseismic events recorded on monitoring arrays are usually contaminated with strong noise. With a low signal-to-noise ratio (S/R), the detection of microseismic events is challenging using conventional detection methods such as the short-term average/long-term average (STA/LTA) technique. Common machine learning methods, e.g., feature extraction plus support vector machine (SVM) and convolutional neural networks (CNNs), can achieve higher accuracy with strong noise, but they are usually time-consuming and memory-intensive to run. We propose the use of YOLOv3, a state-of-art real-time object detection system in microseismic event detection. YOLOv3 is a one-stage deep CNN detector that predicts class confidence and bounding boxes for images at high speed and with great precision. With pre-trained weights from the ImageNet 1000-class competition dataset, physics-based training of the YOLOv3 algorithm is performed on a group of forward modeled synthetic microseismic data with varying S/R. We also add randomized forward-modeled surface seismic events and Gaussian white noise to generate ``semi-realistic'' training and testing datasets. YOLOv3 is able to detect weaker microseismic event signals with low signal-to-noise ratios (e.g., S/N=0.1) and achieves a mean average precision of 88.71\% in near real time. Further work is required to test YOLOv3 in field production settings.

Seismic Moment Tensor Inversion of an Induced Microseismic Event, Offshore Norway: An Insight into the Possible Cause of Wellbore Liner Failure during a Drilling Operation

A microseismic event with Mw∼0.8 was recorded at the Grane oilfield, offshore Norway, in June 2015. This event is believed to be associated with a failure of the wellbore liner in well 25/11-G-8 A. The failure mechanism has been difficult to explain from drilling parameters and operational logs alone. In this study, we analyzed the detected microseismic event to shed light on the possible cause of this event. We inverted for the seismic moment tensor, analyzed the S/P amplitude ratio and radiation pattern of seismic waves, and then correlated the microseismic data with the drilling reports. The inverted seismic moment indicates a shear-tensile (dislocation) event with a strong positive isotropic component (67% of total energy) accompanied by a positive compensated linear vector dipole (CLVD) and a reverse double-couple (DC) component. Drilling logs show a strong correlation between high pump pressure and the occurrence of several microseismic events during the drilling of the well. The strongest microseismic event (Mw∼0.8) occurred during peak pump pressure of 277 bar. The application of high pump pressure was associated with an attempt to release the liner hanger running tool (RT) in the well, which had been obstructed. Improper setting of the liner hanger could have caused the forces from the RT release to be transferred to the liner and might have resulted in ripping and parting of the pipe. The possible direct impact of the ripped liner with the formation or the likely sudden hydraulic pressure exposure to the formation caused by the liner ripping may explain the estimated isotropic component in the moment tensor inversion in the well. This impact can promote slip along the pre-existing fractures (the DC component). The presence of gas in the formation or the funneled fluid to the formation caused by the liner ripping may explain the CLVD component.

Distributed acoustic sensing as a tool for exploration and monitoring: a proof-of-concept

We use PoroTOMO experimental data to compare the performance of Distributed Acoustic Sensing (DAS) and geophone data in executing standard exploration and monitoring activities. The PoroTOMO experiment consists of two "seismic systems": (a) a 8.6 km long optical fibre cable deployed across the Brady geothermal field and covering an area of 1.5 x 0.5 km with 100 m long segments, and (b) an array of 238 co-located geophones with an average spacing of 60 m. The PoroTOMO experiment recorded continuous seismic data between March 10th and March 25th 2016. During such period, a ML 4.3 regional event occurred in the southwest, about 150 km away from the geothermal field, together with several microseismic local events related to the geothermal activity. The seismic waves generated from such seismic events have been used as input data in this study. For the exploration tasks, we compare the propagation of the ML 4.3 event across the geothermal field in both seismic systems in term of relative time-delay, for a number of configurations and segments. Defined the propagation, we analyse and compare the amplitude and the signal-to-noise ratio (SNR) of the P-wave in the two systems at high resolution. For testing the potential in monitoring local seismicity, we first perform an analysis of the geophone data for locating a microseismic event, based on expert opinion. Then, we a adopt different workflow for the automatic location of the same microseismic event using DAS data. For testing the potential in monitoring distant event, data from the regional earthquake are used for retrieving both the propagation direction and apparent velocity of the wavefield, using a standard plane-wave-fitting approach. Our results indicate that: (1) at a local scale, the seismic P-waves propagation and their characteristics (i.e. SNR and amplitude) along a single cable segment are robustly consistent with recordings from co-located geophones (delay-times δt ∼ 0.3 over 400 m for both seismic systems) ; (2) the interpretation of seismic wave propagation across multiple separated segments is less clear, due to the heavy contamination of scattering sources and local velocity heterogeneities; nonetheless, results from the plane-wave fitting still indicate the possibility for a consistent detection and location of the event; (3) at high-resolution (10 m), large amplitude variations along the fibre cable seem to robustly correlate with near surface geology; (4) automatic monitoring of microseismicity can be performed with DAS recordings with results comparable to manual analysis of geophone recordings (i.e. maximum horizontal error on event location around 70 m for both geophones and DAS data) ; and (5) DAS data pre-conditioning (e.g., temporal sub-sampling and channel-stacking) and dedicated processing techniques are strictly necessary for making any real-time monitoring procedure feasible and trustable.

Application of brittleness index to interpret microseismic event distribution in a hydraulically fractured shale formation

Many factors can impact the location data of microseismic events, including natural fractures, rock lithology, in situ stress, and hydraulic-fracturing parameters. The distribution of microseismic events generally tends toward highly brittle areas or areas with brittle minerals. Moreover, location data of microseismic events lack effective evaluation methods. Therefore, we have developed a method to use lithologic information and prestack seismic data to explain the distribution of well Tian Xing microseismic events. We have analyzed the brittleness of the target formation through the well logs and core. We inverted the Young’s modulus and Poisson’s ratio based on simultaneous amplitude variation with offset inversion by the prestack seismic data. We then computed the 3D brittleness index (BI) property volume by Grieser and Rickman’s method. In addition, the microseismic event distribution and BI map were then combined to show the internal relationship between the two results. We found that the well logs and core analysis demonstrated that the target formation has high brittleness. Generally, areas with more natural fractures have a higher probability of inducing hydraulic fractures. However, the analysis results show that the BI has an impact on the distribution of hydraulic fractures. Therefore, BI explains the reason for the distribution of almost all events in the northeast of the perforation. These observations also supported the concept that microseismic events preferentially grow toward more brittle areas.