scholarly journals Coda-Wave Based Monitoring of Pore-Pressure Depletion-driven Compaction of Slochteren Sandstone Samples from the Groningen Gas Field

2020 ◽  
Author(s):  
Reuben Zotz-wilson ◽  
Nikoletta Filippidou ◽  
Arjan Linden ◽  
Berend Antonie Verberne ◽  
Auke Barnhoorn
2020 ◽  
Author(s):  
Reuben Zotz-wilson ◽  
Nikoletta Filippidou ◽  
Arjan Linden ◽  
Berend Antonie Verberne ◽  
Auke Barnhoorn

2021 ◽  
Author(s):  
Nilgün Güdük ◽  
Annemarie Muntendam-Bos ◽  
Jan Dirk Jansen

<p>The Gutenberg-Richter law describes the frequency-magnitude distribution of seismic events where its slope, the 'b-value', is commonly used to describe the relative occurrence of large and small events. Statistically significant b-value variations have been measured in laboratory experiments, mines, and various tectonic regimes (Wiemer & Wyss, 2002). An inversely proportional dependency of the b-value on the differential stress has been observed across different scales (Amitrano, 2003; Schorlemmer et al., 2005). Layland-Bachmann et al. (2012) have shown that this could explain the observed pattern of induced seismicity spatial-temporal b-value variations in Enhanced Geothermal Systems. In our study, we look for a similar relation applied to the Groningen gas field in the Netherlands.</p><p>It is well known that the poroelastic changes in differential stress during gas extraction are influenced by the offset of the reservoir layer across the fault. Recently, Jansen et al. (2019) and Lehner (2019) proposed an analytical solution for stress changes on offset faults due to reservoir depletion. In a parallel study, we extended this solution to include the development of aseismic slip under slip weakening and the derivation of the onset of seismic slip.<br>We utilize this formulation to derive the onset of seismic slip on theoretical faults of variable fault offset, dip, and reservoir thickness. Subsequently, we map our theoretical faults onto the pre-existing faults in the Groningen gas field, deriving fault segment-specific depletion levels at which the segment would become seismically active. We then simulate reservoir depletion conditions over time and assign an event magnitude to fault segments that move past their seismic activation depletion. To assign a magnitude, we use the observation that b-values are inversely proportional to differential stress, which is governed by the pore pressure depletion. Hence, we assume a simple inverse linear relation with pore pressure depletion. Each event magnitude is then randomly drawn from the probability density function of the Gutenberg-Richter distribution with the b-value assigned.<br>We aim to compare the obtained catalogue and its b-value distribution both in time and space to the observed event-size distribution of the Groningen gas field as derived by Muntendam-Bos and Güdük (EGU abstract 2021).</p>


2020 ◽  
Author(s):  
Hanneke Paulssen ◽  
Wen Zhou

<p>Between 2013 and 2017, the Groningen gas field was monitored by several deployments of an array of geophones in a deep borehole at reservoir level (3 km). Zhou & Paulssen (2017) showed that the P- and S-velocity structure of the reservoir could be retrieved from noise interferometry by cross-correlation. Here we show that deconvolution interferometry of high-frequency train signals from a nearby railroad not only allows determination of the velocity structure with higher accuracy, but also enables time-lapse measurements. We found that the travel times within the reservoir decrease by a few tens of microseconds for two 5-month periods. The observed travel time decreases are associated to velocity increases caused by compaction of the reservoir. However, the uncertainties are relatively large. <br>Striking is the large P-wave travel time anomaly (-0.8 ms) during a distinct period of time (17 Jul - 2 Sep 2015). It is only observed for inter-geophone paths that cross the gas-water contact (GWC) of the reservoir. The anomaly started 4 days after drilling into the reservoir of a new well at 4.5 km distance and ended 4 days after the drilling operations stopped. We did not find an associated S-wave travel time anomaly. This suggests that the anomaly is caused by a temporary elevation of the GWC (water replacing gas) of approximately 20 m. We suggest that the GWC is elevated due to pore-pressure variations during drilling. The 4-day delay corresponds to a pore-pressure diffusivity of ~5m<sup>2</sup>/s, which is in good agreement with the value found from material parameters and the diffusivity of (induced) seismicity for various regions in the world. </p>


2017 ◽  
Vol 96 (5) ◽  
pp. s105-s116 ◽  
Author(s):  
Karin van Thienen-Visser ◽  
Peter A. Fokker

AbstractThe Groningen gas field has shown considerable compaction and subsidence since starting production in the early 1960s. The behaviour is understood from the geomechanical response of the reservoir pressure depletion. By integrating surface movement measurements and modelling, the model parameters can be constrained and understanding of the subsurface behaviour can be improved. Such a procedure has been employed to formulate new compaction and subsidence forecasts. The results are put into the context of an extensive review of the work performed in this field, both in Groningen and beyond. The review is used to formulate a way forward designed to integrate all knowledge in a stochastic manner.


2000 ◽  
Vol 3 (04) ◽  
pp. 342-347 ◽  
Author(s):  
M.H.H. Hettema ◽  
P.M.T.M. Schutjens ◽  
B.J.M. Verboom ◽  
H.J. Gussinklo

Summary The decrease of pore pressure during hydrocarbon production (depletion) leads to compaction of the reservoir, which in turn changes the stresses acting on the reservoir. The prediction of reservoir compaction and its consequences is usually based on laboratory experiments performed under uniaxial strain conditions, i.e., allowing no lateral strain during depletion. Field data of the Groningen gas field (The Netherlands) indicate that the stress development of the field deviates significantly from the stress path under uniaxial strain conditions. Laboratory experiments show that the applied stress path has a strong influence on the depletion-induced compaction behavior. We discuss the consequences of these results for the field compaction behavior by considering the responsible deformation mechanisms active in reservoir and experiment. The new Groningen field data, in combination with our experimental results, provide an explanation for the difference between the prediction of compaction and subsidence based on uniaxial experiments and the measurement of compaction and subsidence in the Groningen field. With the use of the new stress path, the predicted and measured compaction and subsidence are in agreement. Introduction The prediction of the amount of depletion-induced reservoir compaction and its adverse consequences (such as subsidence, casing deformation, and seismicity) requires three types of input parameters: The mechanical behavior of the reservoir rock and the rock surrounding the reservoir, the reservoir stress path induced by the depletion, and the dimension and depth of reservoir and overburden formations. Also, a model is required to upscale the laboratory experiments to predict reservoir compaction and the associated surface or seabed subsidence during and after depletion. The first two types of input parameters (mechanical behavior and stress path) are actually linked: The depletion leads to compaction and deformation of the reservoir, which in turn changes the total stresses acting on the reservoir. It is the combination of pore pressure change and total stress change, which alters (and generally increases) the effective normal and shear stresses acting on the load-bearing grain framework. This results in elastic (recoverable) and inelastic (permanent) deformation which, in turn, has a time-independent component, usually referred to as plasticity, and a time-dependent component, referred to as creep. The bulk rock compaction is the result of the various micro mechanisms activated by the depletion, and their dependence on stress path and stress rate (typically, a few MPa per year), stress level (<100 MPa), and temperature (<200°C) and possibly also pore fluid composition.1–3 Ideally, the laboratory experiments are performed along the same stress path that the reservoir undergoes during depletion. However, the reservoir stress path is not known before depletion starts, and analytical or numerical models for the stress development in depleting reservoirs are very sensitive to the input parameters mentioned earlier. To make things worse, field data describing depletion-induced changes in total stress are very scarce, so only a few case studies are available to guide the design of laboratory experiments. In most studies it is assumed that the reservoir compacts uniaxially; that is, there is only vertical compaction and no horizontal deformation. During uniaxial compaction of sandstone with 10 to 30% porosity, the ratio of change in total horizontal stress per change in pore pressure is typically in the range 0.7 to 0.9.3 For the Groningen gas reservoir (The Netherlands) a similar strategy was followed, and a large amount of uniaxial compaction experiments were performed, partly published.3 The tested rock types ranged from low-porosity (5 to 10%) conglomerates to highly porous (25 to 30%) coarse sandstone. However, the compaction and subsidence prediction based on these uniaxial strain experiments is larger than the measured compaction and subsidence in the Groningen field, and the reason for this is still unknown. This paper describes the important role of stress path in compaction prediction and offers a new explanation for the difference in predicted and measured compaction and subsidence in the Groningen field. We start with an analysis of the changes of the total stresses during reservoir compaction, using basic rock mechanics theory. Then, new field stress data are presented and analyzed to estimate the production-induced stress path of the Groningen gas field. Next, the results of triaxial compaction experiments on Groningen core samples are shown, indicating a strong influence of stress path on compaction. Finally, we discuss the experimental results and the consequences of the stress path to the compaction behavior by considering the underlying compaction mechanisms. Although we discuss only field data and core measurements from the Groningen gas field, we think that our conclusions can be generalized, and may be of value to other studies aimed at the prediction of depletion-induced reservoir compaction. Reservoir Stress Changes During Production Prior to production, the Earth's stress field determines the state of stress in the reservoir. Production causes a decrease of the fluid and/or gas pressure in the pores. These pressure changes also result in changes in the total vertical and horizontal stresses acting on the reservoir. Strong evidence for this comes from the occurrence of seismic events inside and close to compacting reservoirs.4,5 Geertsma6 developed a theory of the subsidence and stress changes associated with reservoir compaction, based on linear poroelastic rock behavior. Regarding the total vertical stress, the depletion-induced stress changes at the axis just above a disk-shaped compacting reservoir can be written as6 Δ σ V = h Δ p r ( 1 − 2 ν 2 − 2 ν ) f ( d r ) . ( 1 )


2017 ◽  
Vol 33 (2) ◽  
pp. 481-498 ◽  
Author(s):  
Julian J. Bommer ◽  
Peter J. Stafford ◽  
Benjamin Edwards ◽  
Bernard Dost ◽  
Ewoud van Dedem ◽  
...  

The potential for building damage and personal injury due to induced earthquakes in the Groningen gas field is being modeled in order to inform risk management decisions. To facilitate the quantitative estimation of the induced seismic hazard and risk, a ground motion prediction model has been developed for response spectral accelerations and duration due to these earthquakes that originate within the reservoir at 3 km depth. The model is consistent with the motions recorded from small-magnitude events and captures the epistemic uncertainty associated with extrapolation to larger magnitudes. In order to reflect the conditions in the field, the model first predicts accelerations at a rock horizon some 800 m below the surface and then convolves these motions with frequency-dependent nonlinear amplification factors assigned to zones across the study area. The variability of the ground motions is modeled in all of its constituent parts at the rock and surface levels.


2021 ◽  
pp. 1-67
Author(s):  
Stewart Smith ◽  
Olesya Zimina ◽  
Surender Manral ◽  
Michael Nickel

Seismic fault detection using machine learning techniques, in particular the convolution neural network (CNN), is becoming a widely accepted practice in the field of seismic interpretation. Machine learning algorithms are trained to mimic the capabilities of an experienced interpreter by recognizing patterns within seismic data and classifying them. Regardless of the method of seismic fault detection, interpretation or extraction of 3D fault representations from edge evidence or fault probability volumes is routine. Extracted fault representations are important to the understanding of the subsurface geology and are a critical input to upstream workflows including structural framework definition, static reservoir and petroleum system modeling, and well planning and de-risking activities. Efforts to automate the detection and extraction of geological features from seismic data have evolved in line with advances in computer algorithms, hardware, and machine learning techniques. We have developed an assisted fault interpretation workflow for seismic fault detection and extraction, demonstrated through a case study from the Groningen gas field of the Upper Permian, Dutch Rotliegend; a heavily faulted, subsalt gas field located onshore, NE Netherlands. Supervised using interpreter-led labeling, we apply a 2D multi-CNN to detect faults within a 3D pre-stack depth migrated seismic dataset. After prediction, we apply a geometric evaluation of predicted faults, using a principal component analysis (PCA) to produce geometric attribute representations (strike azimuth and planarity) of the fault prediction. Strike azimuth and planarity attributes are used to validate and automatically extract consistent 3D fault geometries, providing geological context to the interpreter and input to dependent workflows more efficiently.


Author(s):  
Molly Luginbuhl ◽  
John B. Rundle ◽  
Donald L. Turcotte

A standard approach to quantifying the seismic hazard is the relative intensity (RI) method. It is assumed that the rate of seismicity is constant in time and the rate of occurrence of small earthquakes is extrapolated to large earthquakes using Gutenberg–Richter scaling. We introduce nowcasting to extend RI forecasting to time-dependent seismicity, for example, during an aftershock sequence. Nowcasting uses ‘natural time’; in seismicity natural time is the event count of small earthquakes. The event count for small earthquakes is extrapolated to larger earthquakes using Gutenberg–Richter scaling. We first review the concepts of natural time and nowcasting and then illustrate seismic nowcasting with three examples. We first consider the aftershock sequence of the 2004 Parkfield earthquake on the San Andreas fault in California. Some earthquakes have higher rates of aftershock activity than other earthquakes of the same magnitude. Our approach allows the determination of the rate in real time during the aftershock sequence. We also consider two examples of induced earthquakes. Large injections of waste water from petroleum extraction have generated high rates of induced seismicity in Oklahoma. The extraction of natural gas from the Groningen gas field in The Netherlands has also generated very damaging earthquakes. In order to reduce the seismic activity, rates of injection and withdrawal have been reduced in these two cases. We show how nowcasting can be used to assess the success of these efforts. This article is part of the theme issue ‘Statistical physics of fracture and earthquakes’.


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