One of the major challenges of modern society is the goal of reducing the output of anthropogenic greenhouse gases to the atmosphere. To contribute to this goal, the Netherlands is scaling up the use of geothermal energy (GE), a low-carbon technology that provides heating for infrastructure. Geothermal energy requires the extraction of geothermal fluids from a geologic reservoir to provide heat at the surface, followed by re-injection of the fluid into the subsurface. The re-injection, circulation, and extraction of the fluids affect the local stress conditions and can lead to the generation of low-magnitude seismic events. The detection, characterisation, and interpretation of these events improve the efficiency and safety of geothermal operations. This thesis aims to contribute to the Dutch government’s efforts to upscale the use of geothermal energy by enhancing and extending the existing passive seismic tools for monitoring the safety and efficiency of geothermal energy.

In Chapter 2, we introduce a seismic monitoring workflow to detect and characterise low-magnitude seismic events in noisy environments. We incorporate uncertainties from the open-access regional seismic velocity model into the hypocentre estimations. We apply the workflow to the recorded data from a temporary passive network deployed around the Kwintsheul geothermal operation in South Holland, where one low-magnitude seismic event had previously been reported. The network is located in a high-noise environment, characteristic of most geothermal operations in the Netherlands. Despite the high noise levels, we identify five additional low-magnitude seismic events that occurred close to a local fault and the injection well. These are the first events ever recorded in the region. However, large hypocentre uncertainties—due to limitations in the seismic velocity model and sparse azimuthal coverage—prevent a clear interpretation of the underlying processes. From these two limiting factors, only the velocity model can be refined after an event has been recorded. However, refining the available seismic velocity model implies significant costs, as active seismic sources are usually used.

In Chapter 3, we introduce a workflow for validating the seismic velocity model based on body-wave seismic interferometry as a cost-effective alternative. Our workflow is motivated by the possibility of retrieving virtual-offset reflection responses when seismic energy arrives with near-vertical incidence to the receivers. We apply our workflow using the low-magnitude seismic events that we detected. We find that the P-wave velocity model effectively explains the observed retrieved reflections at shallow depths. In contrast, the available S-wave models do not match the data. We conclude that the P-wave model is reliable for hypocentre studies, but that the S-wave model requires refinement.

In Chapter 4, we address how the network geometry influences the detectability and hypocentre resolution of seismic events and implement a workflow for designing seismic networks. In our workflow, we integrate open-access subsurface information to generate a synthetic earthquake catalogue using knowledge of faults and areas of expected higher seismicity risk. We then apply a non-linear design strategy and a global search algorithm to ensure approximately optimal configurations. Finally, we validate the network designs through synthetic hypocentre inversions. We identify the Dutch North Sea as the area in most need of seismic receivers, due to (i) upcoming carbon capture and storage (CCS) initiatives, (ii) the lowest existing network coverage, and (iii) the potential future use of existing oil-and-gas infrastructure for offshore geothermal-energy developments. We apply our workflow to the K-14 offshore field, where carbon capture and storage is planned. The results show that the optimised networks provide sufficient azimuthal coverage and location accuracy, even under simplified assumptions. This workflow can guide the design of cost effective networks in both onshore and offshore environments.

In Chapter 5, we focus on accurate time synchronization of seismic networks. We introduce a data-driven method to detect and correct clock errors using the time-symmetry of ambient-noise correlations. We apply our method to the IMAGE network in Reykjanes, Iceland, deployed to monitor offshore geothermal activity. Offshore geothermal-energy operations introduce additional challenges due to the need for ocean-bottom seismometers (OBS), which lack direct access to GNSS signals, leading to clock-drift errors that affect event timing and localisation. We show that most OBS in the network experienced clock drift, and some had large initial time offsets. We provide an open-source Python package (OCloC) that implements this method, enabling better timing accuracy and improved hypocentre estimation in future offshore monitoring, which can be applied in future offshore geothermal energy and the upcoming carbon capture and storage operations in the Dutch North Sea.

Together, in this thesis we introduce new or adapted workflows to tackle specific limitations in current low-magnitude seismic monitoring practices. By addressing these challenges, this thesis advances the capabilities of seismic monitoring in both onshore and offshore settings. By improving detection, location, velocity model validation, network design, and timing correction, this thesis contributes to the development of robust and cost effective seismic monitoring systems. These tools support operators and regulators in making informed decisions for the safe and sustainable scaling of geothermal energy and carbon storage in the Netherlands and beyond.

Seismic monitoring is essential for understanding subsurface processes, particularly in geothermal operations where low-magnitude events can provide valuable insights into reservoir behaviour. There are two significant challenges when monitoring the seismicity in Dutch geothermal operations: (1) detecting signals from seismic events as noise levels are typically high in regions hosting geothermal operations, and (2) accurately estimating their corresponding hypocentre and uncertainty. In this study, we present a comprehensive workflow for detecting and characterising low-magnitude seismic events. Specifically, we integrated data preparation, template-matching and machine-learning-based event detection, and probabilistic hypocentre estimation. Applying this workflow to 4 months of recordings in Kwintsheul, Netherlands, we detected 65 events with coherent signals, including six weak seismic events (ML < 0.0) near a local fault and a geothermal injection well. These events suggest the presence of a recurring microseismic sequence previously unreported in the area. However, spatial uncertainties, the short monitoring period, and the limited azimuthal coverage make the nature of these events unclear. Our findings highlight the importance of improving network design and refining velocity models to reduce uncertainties in event locations and magnitudes. The proposed workflow offers a scalable solution for enhancing seismic monitoring, particularly in urban and geothermal settings.

Seismic monitoring plays a critical role in ensuring the safety and effectiveness of carbon capture and storage (CCS) operations, as it offers essential insights into fault stability and potential risks to storage integrity. Focal mechanism analysis provides knowledge on stress field orientation, fault slip directions, and seismic source characteristics, aiding the understanding of subsurface fault dynamics and stress changes within the reservoir. Analysing focal mechanisms of small, local earthquakes before, during and after CO₂ injection is crucial for understanding seismic response and, as a result, assessing the risk of significant future events.

Within the ACT SHARP Storage project framework, a newly compiled detailed earthquake bulletin (Kettlety et al., 2024) and waveforms collected in the North Sea region were utilised to invert for moment tensors. Proposed CO2 storage sites in the North Sea are often located far from existing onshore seismological networks, resulting in sparse records and large azimuthal gaps, leading to significant uncertainties in earthquake parameters estimation, such as epicentre coordinates and hypocentral depth, making it very challenging to discriminate natural and induced events.

To address these limitations, we conducted a synthetic study to optimise the placement of offshore stations to improve the monitoring of CO₂ storage sites. Using the open-source Fomosto package, we modelled seismic responses from various double-couple sources and incorporated noise data from existing OBS deployments in Germany and Denmark. The results highlight optimal station configurations and strategies to enhance seismic monitoring, enabling better recovery of focal mechanisms and detecting micro-seismicity that may constitute induced seismicity or early precursors of CO₂ storage containment failure.

This study provides practical advice on designing robust seismic networks, paving the way for improved stress field knowledge and safer CCS operations in the North Sea.

Lack of data and urban noise pose significant challenges to monitoring anthropogenic seismicity in densely populated areas such as the Randstad region in the Netherlands. We deployed a temporary seismic array to monitor a geothermal doublet located at Kwintsheul, Netherlands. We implement innovative array processing, beamforming, and ML automatic-picking techniques to detect low-magnitude microseismic events that could be obscured by urban noise. Additionally, we propose a novel method to incorporate model uncertainties into hypocenter estimations based on the open-access subsurface information of the Netherlands. Contrary to previous studies, our analysis clearly shows that local low-magnitude seismicity does exist and highlights the value of denser seismic arrays and novel detection techniques for monitoring anthropogenic seismicity. The proposed hypocenter localization aids in avoiding under- or overestimation of location uncertainties, which is crucial for informed decision-making. This study advances seismic monitoring techniques in urban geothermal settings, providing critical data for informed decisionmaking and risk assessment of geothermal operations.

Ocean-bottom seismometers (OBSs) are equipped with seismic sensors that record acoustic and seismic events at the seafloor, which makes them suitable for investigating tectonic structures capable of generating earthquakes offshore. One critical parameter to obtain accurate earthquake locations is the absolute time of the incoming seismic signals recorded by the OBSs. It is, however, not possible to synchronize the internal clocks of the OBSs with a known reference time, given that GNSS signals are unable to reach the instrument at the sea bottom. To address this issue, here we introduce a new method to synchronize the clocks of large-scale OBS deployments. Our approach relies on the theoretical time-symmetry of time-lapse (averaged) crosscorrelations of ambient seismic noise. Deviations from symmetry are attributed to clock errors. This implies that the recovered clock errors will be obscured by lapse crosscorrelations' deviations from symmetry that are not due to clock errors. Non-uniform surface wave illumination patterns are arguably the most notable source which breaks the time symmetry. Using field data, we demonstrate that the adverse effects of non-uniform illumination patterns on the recovered clock errors can be mitigated by means of a weighted least-squares inversion that is based on station-station distances. In addition, our methodology permits the recovery of timing errors at the time of deployment of the OBSs. This error can be attributed to either: i) a wrong initial time synchronization of the OBS or ii) a timing error induced by changing temperature and pressure conditions while the OBS is sunk to the ocean floor. The methodology is implemented in an open-source Python package named OCloC, and we applied it to the OBS recordings acquired in the context of the IMAGE project in and around Reykjanes, Iceland. As expected, most OBSs suffered from clock drift. Surprisingly, we found incurred timing errors at the time of deployment for most of the OBSs.

Decarbonisation of the European economy represents one of the current challenges to both society and the energy sector. The advancement and further application of carbon capture and sequestration (CCS) technologies are crucial components of the EU’s effort to become climate-neutral by 2050. The success of CCS depends heavily on understanding the present-day stress field to anticipate reservoir and cap rock response to fluid injection. Despite its importance, many proposed carbon storage sites in the North Sea are located in areas with little to no borehole stress data available, presenting a significant challenge.

Within the ACT project SHARP Storage framework, we have addressed this gap by generating a comprehensive earthquake bulletin for the North Sea, revealing spatial clusters of seismic events with the majority of earthquakes with ML < 4. Focal mechanisms of earthquakes are excellent indicators of crustal dynamics, which are essential for assessing the present-day stress field. Therefore, to improve the understanding of the in-situ stress conditions, we created a comprehensive workflow to evaluate focal mechanisms based on data from the North Sea (Kettlety et al., 2023). First, we developed a routine for the seismological bulletin to aggregate the recorded earthquakes from international seismological centres. The following step included retrieval of the waveforms from data centres and quality control routines, which included dead channels check, exclusion of files with significant recording gaps and low signal-to-noise ratio, and corrections of errors in the station XML files. Then, a subset of data traces with sufficient quality was selected for moment tensor computations using a Bayesian bootstrap-based probabilistic inversion scheme (see Heimann et al., 2018). Using existing focal mechanism solutions for the North Sea region, we calibrated our processing routine and then applied it to selected earthquakes (after 1990, M > 3.5) to expand the existing focal mechanisms database.

The newly computed focal mechanism solutions provide valuable insight into the present-day stress field in areas outside the main hydrocarbon provinces and improve the risk assessment of ongoing and future CCS projects. Furthermore, we will release our processing workflow as an open-source package and a new focal mechanisms database of the North Sea to establish a standard processing routine that can be readily utilised for similar seismological studies.

Geothermal energy is a cleaner and more sustainable source of power, which plays a key role in the transition to a low-carbon economy. Sustainable and safe exploitation of geothermal resources, however, depends on our ability to understand and manage the associated seismic risks. In 2018, Nature's Heat geothermal project began operations in Kwintsheul, Netherlands, aiming to supply heat to 64 hectares of greenhouses. Between July and October 2019, a temporary seismic array was installed to monitor for possible seismic activity at the site. Microseismic moment-tensor inversion is a valuable tool for understanding the mechanics and structure of geothermal reservoirs, and for optimizing their exploitation. It can be challenging, though, to apply this technique when there are high levels of ambient seismic noise, as is often the case in geothermal operations in densely populated areas. In this study, we evaluate the feasibility of inverting the centroid moment tensor of microseismic events in Kwintsheul, using probabilistic moment-tensor inversions. We first test the probabilistic inversion using synthetic recordings of ambient seismic noise, after which we apply the technique to the low-magnitude (Md=0.16) event recorded on July 14, 2019. Our results give insight into the challenges and limitations of applying moment-tensor inversion to low-magnitude events in the context of geothermal operations in the Netherlands.

The timing of the recordings of ocean-bottom seismometers (OBSs) is critical for accurate earthquake location and Earth model studies. GNSS signals, however, cannot reach OBSs deployed at the ocean bottom. This prevents their clocks from being synchronized with a known reference time. To overcome this, we developed OCloC, a Python package that uses time-lapse cross-correlations of ambient seismic noise to synchronize the recordings of large-scale OBS deployments. By simultaneously quantifying deviations from symmetry of a set of lapse cross-correlations, OCloC recovers the incurred clock errors by means of a least-squares inversion. In fact, because non-uniform noise illumination patterns also break the symmetry of (lapse) cross-correlations, we introduce a distance-based weighted least-squares inversion. This mitigates the adverse effect of the noise illumination on the recovered clock errors. Using noise recordings from the IMAGE project in Reykjanes, Iceland, we demonstrate that OCloC significantly reduces the time and effort needed to detect and correct timing errors in large-scale OBS deployments. In addition, our methodology allows one to evaluate potential timing errors at the time of OBS deployment. These might be caused by incorrect initial synchronization, or by rapidly changing temperature conditions while the OBS is sunk to the sea bottom. Our work advances the use of OBSs for earthquake studies and other applications.

In 2018, the geothermal project Nature's Heat started its operations to supply heat to 64 hectares of greenhouses in Kwintsheul, Netherlands. The operation involves the extraction and reinjection of geothermal fluids at a depth of about 2.4km. Several studies suggested that geothermal operations in these parts of The Netherlands are unlikely to generate felt seismic events (M>2.0); nevertheless, adequate seismic monitoring techniques are essential to guarantee sustainable and safe use of the Dutch subsurface. Between July and October 2019, Delft University of Technology, Seismotech (Greece), and Gastreatment Services BV installed a passive seismic network to monitor the seismic activity over Nature's Heat geothermal reservoir. The seismic network consists of 30 three-component short-period seismic sensors placed at inter-station distances of approximately 150 m along two crossing lines. A challenge for seismic monitoring systems in urban areas is the high level of background noise. In Kwintsheul, anthropogenic noise dominates the spectrograms at frequencies higher than 2 Hz. Despite these high background-noise levels, a seismic event of ML = 0.0 (duration magnitude Md 0.16) was recorded by all seismometers of the array on July 14, 2019. To understand the relation of the event and improve the safety of the geothermal operation, we are developing a probabilistic monitoring and inversion scheme. This study aims to improve the seismic network's detection and hypocentre-determination capabilities and verifies via template matching if the detected seismic event is repeating over time (possibly at the background noise level).

The Mutatá earthquake is a Mw 6 earthquake which occurred in northwestern Colombia on September 14, 2016. This region is located at the junction between three tectonic plates, namely the South American, Nazca and Caribbean plates, and the Chocó-Panamá and Northern Andes Blocks. This event took place in the Murindo seismic zone, a zone characterized by a high seismic activity involving the Uramita fault zone, which defines the contact between the two blocks. In this study, we relocate the mainshock – aftershocks sequence and analyze the source characteristics of the Mutatá earthquake. Using data from the Colombian Seismological National Network, and after re-picking the 411 events, we obtain absolute locations exhibiting a NW-SE oriented cloud, with the mainshock being located 8 km away from its original location and at a depth of 17.6 km. The event cloud is situated at the intersection of three faults with different orientations, the NNW-SSE Uramita Fault, a NW-SE fault, and a NNE-SSW inferred fault. Using data coming from 8 broad-band seismographs within 300 km of the mainshock, we perform moment tensor and kinematic slip distribution inversions. The moment tensor inversion points to an event centroid at 20 km depth, with a predominantly double-couple mechanism. The fault orientations in the area, NW-SE orientation of the event cloud, and hypocenter – centroid technique, indicate that the NW-SE nodal plane likely corresponds to the fault plane giving a right-lateral strike-slip mechanism on a SW dipping plane. The rupture model estimated on this plane shows different slip patches, one being close to the mainshock centroid, and few other patches distributed around the mainshock except to the southeast where most of the aftershocks are located. The maximum slip for this model is approximately 0.16 m. The source characteristics of the 2016 Mutatá earthquake suggest then that secondary faults within the Murindo seismic zone can generate large earthquakes, potentially consisting in an important source of seismic hazard in this region.

In 2018, a geothermal doublet started operating in Kwinstheul, Netherlands, for supplying heat to 64 hectares of greenhouses corresponding to Nature’s Heat joint initiative. This kind of geothermal operation requires extraction, circulation, and reinjection of fluids at a depth of 2.4 km. The reservoir used for the geothermal operation has shown good hydraulic parameters which allow the circulation of the fluid. Several authors agree that this kind of geothermal operation is unlikely to generate felt seismicity, nevertheless, adequate seismic monitoring is critical to guarantee sustainable and safe use of the subsurface. To monitor the operation of Nature’s Heat project, 30 three-component short-period seismic sensors were installed by Delft University of Technology and Seismotech (Greece). A challenge for seismic monitoring in Kwinstheul is the high levels of seismic noise coming from anthropogenic and operational activities. Despite the high background noise levels, a seismic event of Md 0.16 was recorded on July 14, 2019. To understand the relation of the event and improve the safety of the geothermal operation, we are developing an optimized monitoring scheme.

Accurate timing of seismic records is essential for almost all applications in seismology. Wrong timing of the waveforms may result in incorrect Earth models and/or inaccurate earthquake locations. As such, it may render interpretations of underground processes incorrect. Ocean bottom seismometers (OBSs) experience clock drifts due to their inability to synchronize with a GNSS signal (with the correct reference time), since electromagnetic signals are unable to propagate efficiently in water. As OBSs generally operate in relatively stable ambient temperature, the timing deviation is usually assumed to be linear. Therefore, the time corrections can be estimated through GPS synchronization before deployment and after recovery of the instrument. However, if the instrument has run out of power prior to recovery (i.e., due to the battery being dead at the time of recovery), the timing error at the end of the deployment cannot be determined. In addition, the drift may not be linear, e.g., due to rapid temperature drop while the OBS sinks to the seabed. Here we present an algorithm that recovers the linear clock drift, as well as a potential timing error at the onset.

The algorithm presented in this study exploits seismic interferometry (SI). Specifically, time-lapse (averaged) cross-correlations of ambient seismic noise are computed. As such, virtual-source responses, which are generally dominated by the recorded surface waves, are retrieved. These interferometric responses generate two virtual sources: a causal wave (arriving at a positive time) and an acausal wave (arriving at a negative time). Under favorable conditions, both interferometric responses approach the surface-wave part of the medium's Green's function. Therefore, it is possible to calculate the clock drift for each station by exploiting the time-symmetry between the causal and acausal waves. For this purpose, the clock drift is calculated by measuring the differential arrival times of the causal and acausal waves for a large number of receiver-receiver pairs and computing the drift by carrying-out a least-squares inversion. The methodology described is applied to time-lapse cross-correlations of ambient seismic noise recorded on and around the Reykjanes peninsula, SW Iceland. The stations used for the analysis were deployed in the context of IMAGE (Integrated Methods for Advanced Geothermal Exploration) and consisted of 30 on-land stations and 24 ocean bottom seismometers (OBSs). The seismic activity was recorded from spring 2014 until August 2015 on an area of around 100 km in diameter (from the tip of the Reykjanes peninsula).

In volcanic and hydrothermal geosystems, monitoring of mass and stress changes provide information for both volcanic hazardassessment and estimation of geothermal resources. The combined continuous recording of the gravity field and ground motionwith sufficient accuracy in an active volcano-tectonic setting allows a better understanding of the mass and stress transfermechanisms that produce short term gravity changes and local seismic activity. The aim is to gain a better understanding ofgeothermal system processes by addressing short-term mass changes within geothermal reservoirs in relation to external influencessuch as anthropogenic (reservoir exploitation) and natural forcing (local and regional earthquake activity and earth tides). Thiscontributes to knowing the reservoir properties, structure and long-term behaviour.Þheistareykir (Northeast Iceland), where the geothermal power production started in autumn 2017 (2x45 MWe) is the site chosenfor this unique experiment. The overall goal of the project is to use a network of continuously measuring gravity meters to detectsmall variations in gravity associated with managing a geothermal field (injection and extraction). The gravity changes are expectedto be small: ~5 µgal/6 months (1 µgal=10-8 ms-2). Therefore, high performance and up-to-date instrumentation such assuperconducting gravity meters (SG), spring gravity meters and broadband seismometers are used. To achieve these goals, inautumn 2017 a network of 5 relative gravity meters (3 iGravs and 2 gPhones) and 14 seismic stations were deployed. Three gravitymonitoring sites are in close vicinity to the production and injection area, and one iGrav is set up outside the geothermal field forreference. Presented in this report are the details of the infrastructure and instruments deployed and the first results of more than 18months of continuous gravity and seismicity monitoring.

In volcanic and hydrothermal systems, monitoring of mass and stress changes by continuous gravity field and ground motion records provides information for both volcanic hazard assessment and estimation of geothermal resources. We aim at a better understanding of volcanic and geothermal system processes by addressing mass changes in relation with external influences such as anthropogenic (reservoir exploitation) and natural forcing (local and regional earthquake activity, earth tides). Þeistareykir is a geothermal field located within the Northern Volcanic Zone (NVZ) of Iceland on the Mid-Atlantic Ridge. Geothermal power production started in autumn 2017. For the first time on a geothermal production field, we deployed a network of 4 continuously recording gravity meters (3 superconducting meter, iGrav and one spring gravity meter gPhone) in order to cover the spatial and the temporal changes of gravity and to detect small variations related to the geothermal power plant operation (e.g. extraction and injection). All gravity monitoring stations are equipped with additional instrumentation to measure parameters that may affect the gravity records (e.g. GNSS and hydrometeorological sensors). Additionally, we deployed a temporal seismic network consisting of 14 broadband stations to enhance the seismic activity monitoring of the permanent Icelandic network in this very active region of the NVZ. Results of this unique experiment contribute to determine reservoir properties and main structures and may also reveal details of active tectonic processes. Here, we present the instrumental setup at the site and first results of more than 24 months of continuous gravity and seismicity records.

Colombia is located on the South American plate with two zones of subductions, one to the west on the Pacific side (Nazca plate), and one to the North on the Caribbean side (Caribbean plate). This leads to the presence to large and complex fault system within Colombia. On September 14, 2016, a Mw 6.0 earthquake occurred in Northwestern Colombia on the Uramita fault close to Mutata at a depth of approximately 18 km. The moment tensor calculated by the USGS for this event shows a thrust fault focal mechanism with a fault plane dipping at 35° and a small right-lateral component. Interestingly, the moment tensor decomposition shows a double couple component of only 55%. This event is both one of the most superficial and one of the strongest seismic events that occurred in Colombia since the installation of the national seismological network (RSNC) in 1993. In this work, we invert for the slip distribution on the fault plane for this seismic event using a combination of broad-band and near-field data provided by the USGS and the RSNC. We first choose the fault plane using the moment tensor and the information on the fault system available. The fault plane is then divided in a number of rectangular sub-faults in order to calculate the contributions of slip from each patch in the source region. To solve the slip inversion, we finally use the multiple shock sequence method with a least-squares fit. The slip distribution is also compared with the aftershocks distribution in order to investigate their coseismic triggering by the mainshock. Very few earthquakes from Colombia were studied in order to determine their slip distribution. This study is then a first step toward a better understanding of their complex rupture, and to better estimate seismic hazards in the region.

Even though the amount and quality of data now available for seismologists is increasing in Colombia, seismic or GPS stations near the event are usually unavailable. For this reason, the usage of far-field stations is necessary especially for procedures such as slip inversion. In the present study, we investigate the slip distribution for the Mutata earthquake, Colombia. This is one of the strongest and shallowest events that had occurred in Colombia in the past few decades. On September 14, 2016, a Mw 6.0 earthquake occurred in Northwestern Colombia on the Uramita fault very close to a small town called Mutata, nearby Medellín. The event occurred at a depth of 18km in the proximity of both, the Nazca - South America subduction zone (to the west) and the Caribbean - South America subduction zone (to the North). The USGS moment tensor given for this event shows a thrust fault focal mechanism with a strike of 121º and dipping at 35º.

To calculate the slip distribution, we merged different functions from ObsPy, MudPy and Syngine in order to retrieve, process and invert the broadband seismic data provided by the USGS and the RSNC (Red Sismológica Nacional de Colombia) including near- and far-field stations. First, we defined the fault plane for inversion using the moment tensor and regional geologic information. We then divided the fault plane into 300 rectangular subfaults in order to calculate the slip amplitude for each patch in the source region. The green functions and synthetics are calculated using different codes for the far-field (Syngine) and the near field (MudPy), both applying a triangle source time function with different durations to identify the correct rise time and fall time for this event. The synthetics and observed seismic signals are finally processed using ObsPy and the inversion is done using MudPy. After calculating the slip distribution, we find two main asperities at depths of approximately 20km with a maximum slip of about 20 cm. The two asperities are located on the left and right sides of the mainshock hypocenter. The aftershocks are first relocated and then compared with the slip distribution in order to investigate coseismic triggering by the mainshock. This kind of study is one of the first carried out for a Colombian earthquake and will help to better define fault systems and seismic hazard in this area.