Seismic imaging and monitoring with reflected waves, originally used in the oil and gas industry to identify and assess potential hydrocarbon reservoirs and later monitor their exploitation, also have diverse applications in near-surface geophysics, mineral exploration, geothermal energy, and CO2 or H2 storage. Beyond revealing subsurface structures, these techniques enhance our understanding of how the subsurface responds to human activities, such as induced seismicity due to extraction processes. Seismic imaging and monitoring often focus on specific target layers within the subsurface, but challenges from interferences with surrounding layers and small changes within the specific layer(s) can distort the specific signals and lower the accuracy. Our research aims to address these challenges and provide practical solutions for more accurate and reliable seismic imaging and monitoring with reflected waves.
In this thesis, we aim to develop seismic data-driven methods for layer-specific imaging and monitoring, with a primary focus on advancing the technique of ghost-reflection retrieval using seismic interferometry (SI) and showing how the Marchenko method could be used with land seismic data.
SI often involves the cross-correlation of seismic observations at different receiver locations and the consecutive summation over the available sources, allowing the retrieval of new seismic responses from virtual sources located at the receiver positions. When using sources and receivers only at the surface, the virtual-source gathers retrieved by SI contain not only pseudo-physical reflections but also ghost (non-physical) reflections. These ghost reflections result mainly from the cross-correlation (CC) or auto-correlation (AC) of primary reflections from two different depths, representing reflections from inside specific subsurface layer(s), as measured with a virtual ghost source and a virtual ghost receiver positioned directly on top of the specific layer(s). Consequently, the ghost reflections can provide information about the specific layer(s) without the effects of the overburden and underburden layers.
We first explore the use of ghost reflections for layer-specific characterisation of the shallow subsurface using SI by AC, utilising numerically modelled data for a layered subsurface model down to 30 m depth, incorporating a lateral change in velocity, a velocity gradient with depth, a thickness change, and a velocity change in the target layer. Additionally, we present the first application of ghost reflections to shallow subsurface field data. Ghost reflections typically exhibit similar characteristics to other reflection events, appear close to or interfere with other events with only slight temporal differences. This makes their identification a significant challenge. To address this, we eliminate surface-related multiples and demonstrate how specific ghost reflections can be more efficiently retrieved by muting undesired reflections in the dataset before applying SI.
To extend the application of ghost reflections to deep structures, we focus on the feasibility of monitoring pore-pressure changes in the Groningen gas field in the Netherlands. We utilise numerical modelling to simulate scalar reflection data, deploying sources and receivers at the surface. We conduct an ultrasonic transmission laboratory experiment to measure S-wave velocities at different pore pressures. This data is used to create subsurface models, which are then utilized to simulate scalar reflection seismic data for monitoring purposes. We retrieve zero-offset ghost reflections by applying SI by AC to the modelled datasets. We then use a correlation operator to determine time differences between a baseline survey and monitoring surveys. Additionally, we investigate the effects of the sources and receivers' geometry and spacing, as well as the number of virtual sources and receivers, on retrieving ghost reflections with high interpretability and resolution. Besides observing time shifts in the ghost reflections, we also explore the feasibility of using the amplitude of ghost reflections for reservoir monitoring.
Having clear reflections from both the top and bottom of the specific layer(s) is crucial for retrieving ghost reflections, which can be challenging when using land seismic datasets due to the usual presence of strong surface waves. Conventionally, surface waves are suppressed during data processing using frequency-offset, frequency-wavenumber, or bandpass filters. However, these approaches can prove ineffective when the surface waves are scattered and/or overlap with the frequency regions of the reflected body waves that we intend to preserve. To overcome some of these challenges, we show the efficacy of the interferometric surface-wave suppression using a 2D seismic reflection dataset from Scheemda, Groningen province, the Netherlands. Interferometric surface-wave suppression can be used to effectively suppress surface waves by applying SI to first estimate the surface waves and second followed by their adaptive subtraction from the original data. We propose to apply these two steps recursively, i.e., several times, which yields better results than a single application in terms of clearer and more continuous reflections. This technique can function as a standalone technique or as part of a pre-processing flow.
When applying the seismic reflection method for monitoring purposes, specific reflections, e.g., from the top and bottom of the reservoir, are of interest. The reflections from both the top and bottom of the specific layer(s) can also be distorted by other events from the surrounding layers. To eliminate such distortions, the Marchenko-redatuming method was introduced. Several Marchenko-redatuming methods have been applied successfully to marine field data. We demonstrate, for the first time, the application of the Marchenko-based isolation technique to field land seismic data to isolate the target response by removing the overburden and underburden. Land data are intrinsically elastic, known for dominant surface waves and a low signal-to-noise ratio, posing a challenge for the Marchenko method, which requires high-quality reflection data. After we carefully apply several pre-processing steps, including recursive interferometric surface-wave suppression, we apply the Marchenko method twice: first, to remove the overburden effects by choosing a focal depth of 30 m, and then to remove the underburden effects by choosing a focal depth of 270 m. This process generates a new reflection response from the target area, providing clearer subsurface responses. The Marchenko method is particularly beneficial for data-driven techniques such as ghost-reflection retrieval, seismic imaging, and time-lapse studies using land seismic datasets.@en

Seismic interferometry (SI) retrieves the Green function between two receiver locations using their recordings from a boundary of sources. When using sources and receivers only at the surface, the virtual-source gathers retrieved by SI contain pseudo-physical reflections as well as ghost (non-physical) reflections. These ghost reflections are the results of the cross-correlation or auto-correlation (AC) of primary reflections from two different depth levels, and they contain information about the seismic properties of specific layers in the subsurface. We investigated the application of ghost reflections for layer-specific characterization of the shallow subsurface using SI by AC. First, we showed the technique's potential using synthetic data for a subsurface model with a lateral change in velocity, a gradient in depth for velocity, a thickness change and a velocity change of the target layer. Then, we applied the technique to shallow subsurface field data. We also focused on improving the retrieval of ghost reflections by removing the free-surface multiples and muting undesired events in active-source gathers before applying SI. Our results demonstrate that the ghost reflections can be used advantageously to characterize the layer that causes them to appear in the results of SI. Consequently, they can also provide valuable information for imaging and monitoring shallow subsurface structures.

@en

The Marchenko method is capable of estimating Green’s functions between the surface of the Earth and arbitrary locations in the subsurface. These Green’s functions are used to redatum wavefields to a deeper level in the subsurface. The Marchenko method enables the isolation of the response of a specific layer or package of layers, free from the influence of the overburden and underburden. In this study, we apply the Marchenko-based isolation technique to land S-wave seismic data acquired in the Groningen province, the Netherlands. We apply the technique for combined elimination of the overburden and underburden. Our results indicate that this approach enhances the resolution of reflection data. These enhanced reflections can be utilised for imaging and monitoring applications.@en

Seismic interferometry (SI) retrieves new seismic responses, for example reflections, between either receivers or sources. When SI is applied to a reflection survey with active sources and receivers at the surface, non-physical (ghost) reflections are retrieved as well. Ghost reflections, retrieved from the correlation of two primary reflections or multiples from two different depth levels, are only sensitive to the properties in the layer that cause them to appear in the result of SI, such as velocity, density and thickness. We aim to use these ghost reflections for monitoring subsurface changes, to address challenges associated with detecting and isolating changes within the target layer in monitoring. We focus on the feasibility of monitoring pore-pressure changes in the Groningen gas field in the Netherlands using ghost reflections. To achieve this, we utilize numerical modelling to simulate scalar reflection data, deploying sources and receivers at the surface. To build up subsurface models for monitoring purposes, we perform an ultrasonic transmission laboratory experiment to measure S-wave velocities at different pore pressures. Applying SI by autocorrelation to the modelled data sets, we retrieve zero-offset ghost reflections. Using a correlation operator, we determine time differences between a baseline survey and monitoring surveys. To enhance the ability to detect small changes, we propose subsampling the ghost reflections before the correlation operator and using only virtual sources with a complete illumination of receivers. We demonstrate that the retrieved time differences between the ghost reflections exhibit variations corresponding to velocity changes inside the reservoir. This highlights the potential of ghost reflections as valuable indicators for monitoring even small changes. We also investigate the effect of the sources and receivers’ geometry and spacing and the number of virtual sources and receivers in retrieving ghost reflections with high interpretability resolution.

@en

High-resolution seismic reflections are essential for imaging and monitoring applications using data-driven methods such as seismic interferometry (SI) and Marchenko redatuming. For seismic land surveys using sources and receivers at the surface, the surface waves are the dominant noises that mask the reflections. We use SI to suppress surface waves from the reflection dataset. SI is a technique that allows the retrieval of new seismic responses at one receiver from a virtual source at the position of another receiver using, e.g., cross-correlation or convolution. We processed a two-dimensional seismic reflection dataset acquired along a line in Scheemda, located in the Groningen province of the Netherlands. The sources are placed with a spacing of 2 m, and 601 receivers are placed every 1 m. We implemented some pre-processing steps, including source signature deconvolution and filtering. Then, we applied SI by cross-correlation by turning receivers into virtual sources to estimate the dominant surface waves. Afterwards, we performed adaptive subtraction with different filter parameters for the matching filter to minimise the difference between the surface waves in the original data and the result of SI. Comparing the retrieved results from SI with the original data in the time domain and the frequency-wavenumber domain shows that at least some parts of surface waves are suppressed from the dataset, which can help to better visualise reflections for future studies in imaging and monitoring the subsurface. @en

Seismic interferometry (SI) retrieves new seismic responses between receivers or sources using, e.g., cross-correlation. Applying SI to a reflection survey with active sources and receivers at the surface, one retrieves ghost reflections besides the physical reflections. Ghost reflections are retrieved from the correlation of two primary reflections or multiples from two different depth levels. They are only sensitive to the changes in the layer that cause them to appear in the result of SI. Using ghost reflections from SI, we investigate the possibility of monitoring pore-pressure depletion due to gas extraction in the Groningen gas field, Netherlands. We performed an active-source transmission laboratory experiment to measure S-wave velocities at pore pressures of 50, 80, 100, 200, and 300 bar. Using these values; we numerically model scalar reflection data with sources and receivers at the surface for the Groningen subsurface model. Applying SI by auto-correlation to these datasets, we retrieve zero-offset ghost reflections. We show that using only the reflections from the top and the bottom of the reservoir is essential for retrieving a specific ghost reflection from inside the reservoir. The retrieved ghost reflections showed clear time differences, indicating they can be utilized to monitor reservoir pore-pressure depletion changes.@en

Seismic interferometry (SI) is a method that retrieves new seismic traces from the cross-correlation of existing traces, where one of the receivers acts as a virtual seismic source whose response is retrieved at other receivers. When using sources only at the surface, and so-called one-sided illumination of the receivers occurs, not only desired physical reflections are retrieved, but also non-physical (ghost) reflections. These non-physical reflections are caused by internal reflections inside subsurface layers. They are thus particularly interesting to use for monitoring changes in the specific subsurface layer that causes them to appear in the SI result because they could provide valuable information about the physical properties of the subsurface. We illustrate the potential of SI with active-source data from numerical acoustic modelling using the Groningen subsurface model. This model describes the natural gas field located in the Groningen province in the northeastern part of the Netherlands. The reservoir of the Groningen gas field is located at depths between 2600 m and 3200 m, the total thickness ranges from approximately 100 m to 300 m. The Groningen field is cut by several fault systems, subdividing the field into a large number of fault blocks, and it is a clear example of induced seismicity by gas production. We investigate the utilization of non-physical reflections retrieved from surface active-source data using SI by cross-correlation and auto-correlation. With multi-offset gathers, besides physical reflections, we retrieve non-physical reflections as well; by muting undesired reflections, we can retrieve better target-related non-physical reflections. To illustrate the potential of the non-physical reflections for monitoring purposes, we apply velocity changes in the Groningen reservoir. With zero-offset gathers, which are retrieved from SI by auto-correlation, we show that in case of velocity changes, the non-physical reflections show a clear change; furthermore, they show a good agreement with the geometry of specific subsurface layers, specifically with the faulted structure. Thus, we can utilize non-physical reflections for imaging and monitoring in the Groningen reservoir.@en

Seismic interferometry (SI) is a method that retrieves new seismic traces from the cross-correlation of existing traces, where one of the receivers acts as a virtual seismic source whose response is retrieved at other receivers. When using sources only at the surface, and the so-called one-sided illumination of the receivers occurs, we will retrieve not only the desired physical reflections but also non-physical (ghost) reflections. These non-physical reflections appear due to waves that propagate inside a subsurface layer. Thus, they contain information about the seismic properties of the specific layer. We illustrate the technique’s potential using numerically modelled data for a subsurface model with a low-velocity layer, which is also pinching out, and near-surface field data. We apply SI by cross-correlation and auto-correlation. Both resulting non-physical reflections are sensitive to the physical rock properties of the layer that causes them to appear in the SI results. Moreover, non-physical reflections in zero-offset gathers that result from SI by auto-correlation show very good conformity with the geometry of the subsurface layers.@en

Seismic interferometry (SI) refers to the principle of generating seismic responses by crosscorrelating seismic observations at different receiver locations. Theory requires that the boundary sources emit the same energy, have regular spacing and are spaced densely enough. When these assumptions are not met, not only the desired physical reflections will be retrieved, but also non-physical (ghost) arrivals, including reflections. This is a result of insufficient destructive interference. The non-physical reflections are caused by internal reflections inside subsurface layers, and they are particularly important for monitoring changes in the specific subsurface layer that causes them to appear in the SI results. We test this concept on data from numerical modelling using a subsurface model of the Groningen gas field for purposes of the DeepNL programme. The Rotliegend reservoir is located at depths between 2600 m and 3200 m, the total thickness of the Rotliegend in the Groningen field ranges from approximately 100 m to 300 m. The Groningen field is cut by several fault systems, subdividing the field into a large number of fault blocks. We investigate utilization of non-physical reflections in multi-offset gathers and zero-offset gathers. From the multi-offset gathers, which are retrieved from SI by crosscorrelation, we show that in case of changes in the velocity and thickness of the Groningen reservoir, the non-physical reflections show a clear change. Furthermore, we show that the changes can be quantified. Thus, they can be used for monitoring purposes in the subsurface layers. The non-physical reflections in zero-offset gathers show very good conformity with the geometry of the specific subsurface layer, thus allowing imaging, e.g., of faults. @en

Seismic interferometry (SI) refers to the principle of generating new seismic responses using crosscorrelations of existing wavefield recordings. In this study, we report on the use of a specific interferometric approach, called seismic interferometry by multidimensional deconvolution (SI by MDD), for the purpose of retrieving surface-wave responses. In theory, SI by MDD suffers less from irregularities in the distribution of (passive) sources than conventional SI. Here, we confirm this advantage for the application to surface waves originating from regional earthquakes close to Central Chile. For that purpose, we use the Malargüe seismic array in Argentina. This T-shaped array consists of two perpendicular lines of stations, which makes it rather suitable for the application of SI by MDD. Comparing the responses retrieved through SI by MDD to the responses retrieved using conventional SI, we find that the application of SI by MDD results in surface-wave responses that are both more accurate and more stable than surface-wave responses that are retrieved using conventional SI. That is, our results demonstrate that SI by MDD suffers less from non-uniformly distributed earthquakes and differences in the power spectra of earthquake responses. In addition, we show that SI by MDD mitigates the effect of site amplification on the retrieved surface waves.@en

Seismic interferometry (SI) is a principle for retrieving responses between two receivers using cross-correlation. After the retrieval, one of the receivers acts as a virtual seismic source whose response is retrieved at the second receiver. Correct response retrieval relies on assumptions, among other, of a lossless medium being illuminated homogeneously by sufficiently densely spaced sources (passive or active). When these assumptions are not met, non-physical reflections might appear in the results of SI due to insufficient destructive interference. These non-physical reflections are caused by internal reflections inside subsurface layers. However, the non-physical reflections could be used for monitoring changes in the subsurface layers that generate them. We investigate utilization of non-physical reflections for monitoring velocity changes for purposes of the DeepNL programme. We simulate reflection experiments using an acoustic finite-difference modelling for a horizontally layered model and for a subsurface with inclined layers. We perform SI by autocorrelation and by cross-correlation. Comparing retrieved results with the directly modelled results, we confirm previous results that for a layered subsurface the retrieved ghost reflections can be used for multiple offsets. For inclined layers, zero-offset ghost reflections can be retrieved for the different receiver locations. Both types of non-physical reflections are sensitive to velocity change and thickness of the layer that cause them to appear in the SI results, so they can be used for monitoring purposes of the subsurface. @en