DAS Preprocessing Workflow

This report addresses deliverable D1.4 of the DigiMon project, which covers the preprocessing workflow for datasets acquired by Distributed Acoustic Systems (DAS). The workflow seeks to capture the key stages required to prepare the raw seismic data for the main processing stages and demonstrates their application using both synthetic and real-world data. A description of the synthetic datasets can be found in DigiMon deliverable D1.3 report, while details of the real-world datasets are included in DigiMon reports D1.1 and D1.2

DAS field dataset to compare technologies and deployment scenarios – Antarctica Dataset

This report describes a Distributed Acoustic Sensing (DAS) dataset acquired by the British Antarctic Survey (BAS) and the University of Oxford in Antarctic during 2020. The field dataset contributes to the Deliverable D1.1 of the DigiMon project (DAS field dataset to compare technologies and deployment scenarios), which is associated with tasks 1.2 and 1.3 of the project

DAS dataset suitable for microseismic and ANI analysis

Deliverable 1.2 concerns a DAS dataset suitable for microseismic and ambient noise interferometry (ANI). For this deliverable the DAS field dataset of FORGE is recommended. FORGE is the Frontier Organization For Research in Geothermal Energy, and is a field laboratory for developing an enhanced geothermal system in hot crystalline rock situated near the town of Milford in Utah, USA (https://utahforge.com/). The FORGE team is led by Joe Moore of Utah (and funded by the US Department of Energy) and is credited for this dataset. The dataset is completely open access, but obviously attribution would be appreciated in any publications. The FORGE dataset applies for deliverable 1.2, because it provides downhole DAS and geophone recordings of microseismic events, and covers approximately two weeks of continuous DAS recordings that can be used to test the potential of DAS for the ANI method. In addition to the FORGE dataset, various other DAS datasets have recently become publicly available that are recommended to consider as well for further work in task 1.3 and associated tasks, since they can be valuable in addressing different research aspects of the application of DAS. Table 1.1 gives a summary of the different open access datasets considered for this deliverable. This table also shows whether the datasets are suitable to be used for microseismic and ANI analysis. With this application in mind for deliverable 1.2, and when compared against alternative datasets (see Table 1.1), the FORGE dataset is considered to be especially relevant for this deliverable, since it provides both microseismic event data and continuous DAS recordings from a borehole configuration spanning a relatively long duration (17 days). The borehole configuration is preferable for the purpose of detecting micro-seismicity since it allows measurements close to the reservoir and therefore able to detect weaker events compared to a trenched deployment at the surface. FORGE concerns an enhanced geothermal system and in this setting the mechanism driving seismicity is different compared to the case of CO2 injection and storage (DIGIMON). However, the performance of the DAS cable with respect to detected seismicity is expected to be similar for the case of monitoring CO2 injection and storage as in a geothermal setting and therefore the FORGE dataset is expected to be suited for this purpose

DAS field dataset to compare technologies and deployment scenarios

This report describes a Distributed Acoustic Sensor (DAS) dataset acquired by DigiMon partners at the Containment and Monitoring Institute’s (CaMI) Field Research Station (FRS), Canada, between 6th to 10th September 2021. The field dataset contributes to the Deliverable D1.1 of the DigiMon project (DAS field dataset to compare technologies and deployment scenarios), which supports tasks 1.2 and 1.3 of the project. The objective of the DigiMon project is to develop an early-warning system for Carbon Capture and Storage (CCS), which utilises a broad range of sensor technologies including DAS. While the system is primarily focused on CCS projects located in shallow offshore environment of the North Sea, it is also intended to be adaptable to onshore settings. Some of the key areas that the systems will monitor include the movement of the plume within the reservoir, well integrity, and CO2 leakage into the overburden. A combination of both active and passive seismic methods will be deployed to track the movement of CO2, for example seismic reflection to image seismic velocity changes and microseismics to capture fault activation. Acquiring seismic surveys using DAS is highly novel and offers cost-effective approach which can significantly increase the spatial resolution of the survey data; however, it has had limited use in the operational environment with several technical challenges still needing to be resolved, such as the transfer function of DAS. CaMi FRS was selected as a field test location as the site has been specifically established to advance the development of monitoring technologies and protocols for CCS operations. At CaMi FRS, several different monitoring arrays have been installed which are directly applicable to DigiMon. This includes a 5km loop of DAS optical fibre, located with a 1.1 km surface trench and two observation wells, an array of surface and borehole geophone nodes, and 6 broadband seismometers operating by the University of Bristol. This monitoring infrastructure has been primarily installed to monitor CO2 injections into the Basal Belly River sandstone formation at approximately 300m below ground level. Injection of CO2 began at FRS in 2019 and during this time microseismic events have been recorded, albeit at shallower levels than the injection point. The site therefore provides a potential DAS dataset which contains both active and passive measurements for the DigiMon project. The abundance of instrumentation including DAS, geophones, and broadband seismometers provides a unique chance to test the capacity of these instruments for C02 storage monitoring

Concept description for the use of fibre-optic measurements for seismic tomography

High resolution mapping of CO2 plumes in the geological storage formations can be obtained using cross well seismic experiments designed to characterise velocity changes in the subsurface, see figure 1. High resolution studies are facilitated by using dense measurement surveys with many wireline operations that adjust seismic source and detector positions. Distributed fibre optic acoustic sensing may enhance traditional wireline cross wire surveys by providing an aliasing-free method for characterising seismic waveforms, and potentially enable a reduction in the number of individual measurements (and therefore cost) required for performing cost sensitive CO2 plume surveys. In addition, seismic tomography involving fibre optic receivers and ambient noise techniques, could enable permanent monitoring of subsea CO2 storage with seismic tomography. This document gives a basic concept description of cross-well seismic technology, both with active seismics and ambient noise, and their application with distributed fiber optics sensing. The document also describes the infrastructure for carrying out cross well/fibre optic measurements at Svelvik, and a proposal for a measurement campaign to be carried out as part of the DigiMon project.Concept description for the use of fibre-optic measurements for seismic tomographypublishedVersio

High resolution imaging of the M​L​ 2.9 August 2019 earthquake in Lancashire, UK, induced by hydraulic fracturing during Preston New Road PNR-2 operations

Hydraulic fracturing (HF) at Preston New Road (PNR), Lancashire, United Kingdom, in August 2019, induced a number of felt earthquakes. The largest event (⁠ML 2.9) occurred on 26 August 2019, approximately three days after HF operations at the site had stopped. Following this, in November 2019, the United Kingdom Government announced a moratorium on HF for shale gas in England. Here we provide an analysis of the microseismic observations made during this case of HF‐induced fault activation. More than 55,000 microseismic events were detected during operations using a downhole array, the vast majority measuring less than Mw 0. Event locations revealed the growth of hydraulic fractures and their interaction with several preexisting structures. The spatiotemporal distribution of events suggests that a hydraulic pathway was created between the injection points and a nearby northwest–southeast‐striking fault, on which the largest events occurred. The aftershocks of the ML 2.9 event clearly delineate the rupture plane, with their spatial distribution forming a halo of activity around the mainshock rupture area. Across clusters of events, the magnitude distributions are distinctly bimodal, with a lower Gutenberg–Richter b‐value for events above Mw 0, suggesting a break in scaling between events associated with hydraulic fracture propagation, and events associated with activation of the fault. This poses a challenge for mitigation strategies that rely on extrapolating microseismicity observed during injection to forecast future behavior. The activated fault was well oriented for failure in the regional stress field, significantly more so than the fault activated during previous operations at PNR in 2018. The differing orientations within the stress field likely explain why this PNR‐2 fault produced larger events compared with the 2018 sequence, despite receiving a smaller volume of injected fluid. This indicates that fault orientation and in situ stress conditions play a key role in controlling the severity of seismicity induced by HF

DAS Processing Algorithms

This report addresses deliverable D1.5 of the DigiMon project, which covers processing algorithms for Distributed Acoustic Systems (DAS) datasets that are contained within a python library called DASpy. The objective of DigiMon is to develop an early-warning system for Carbon Capture and Storage (CCS) which utilises a broad range of sensor technologies including DAS. While the system is primarily focused on the CCS projects located in shallow offshore environment of the North Sea, it is also intended to be adaptable to onshore settings. Some of the key areas that the systems will monitor include the movement of the plume within the reservoir, well integrity and CO2 leakage into the overburden. A combination of both active and passive seismic methods will be deployed to track the movement of CO2, for example seismic reflection to image seismic velocity changes or microseismics to capture small earthquakes relating to fault activation

DAS synthetic dataset

Deliverable D1.3 of the ACT DigiMon project is a synthetic microseismic distributed acoustic sensins (DAS) dataset. There are a number of possible uses for such a dataset; for example supporting the development and testing of DAS processing algorithms, testing the efficacy of different array geometries in detecting and characterising events, or simulating a field experiment to better understand observed processes. Given the large number of possible uses it was decided that rather than simply delivering a collection of files of synthetic seismic events, it would be more valuable to deliver a modelling framework from which synthetic data can be generated as the need arises, combined with a small example dataset of a few events to demonstrate the capabilities. DAS systems record seismic wavefields and ground motion due to their sensitivity to strain along the axis of the fibre. To understand the response of DAS it is necessary to understand (1) the seismic source, (2) the path effects and (3) the site and instrument effects. In this report we discuss the modelling of the first two contributions of the DAS response; the source and path effects. We simulate the resulting particle motion and strain at the fibre location, resulting from realistic microseismic sources in geological models representative of the North Sea. The third contribution; site and instrument effects, is contained in the transfer function, which describes the mathematical relationship between the wavefield properties at the cable location to the recorded DAS output. The form of the transfer function is a key unanswered question which will be addressed in Task 1.2 of the DigiMon project

Extending local magnitude ML to short distances

Local magnitudes calculated at stations less than 10 km from earthquakes in the British Isles are up to one unit of magnitude higher than local magnitudes calculated at more distant stations. This causes a considerable overestimate of the event magnitude, particularly for small events, which are only recorded at short distances. Data from Central Italy and Norway show that the same problem also occurs in other regions, suggesting that this is a more general issue for local magnitude scales. We investigate the addition of a new exponential term to the general form of the local magnitude scale. This corrects for the higher-than-expected amplitudes at short hypocentral distances. We find that the addition of this new term improves magnitude estimates in the three studied regions and magnitudes at short distances are no longer overestimated. This allows the use of a single scale that can be used at all distances, with a smooth transition between short and long distances. For the UK, the amended scale is M L =log(amp) +1.11log(r)+0.00189r−1.16e −0.2r −2.09 ML =log⁡(amp) +1.11log⁡(r)+0.00189r−1.16e−0.2r−2.09 and this is the scale now used by the British Geological Survey