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S. Oumejjoud
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Using a field classification, I have assessed the likelihood that a gas field caused a seismic event. I have put the focus on all of the minor gas fields located in the Rotliegend sandstone formation in the Netherlands. These gas fields were divided into five geologically distinctly different regions: the North Holland Platform (NHP), the Groningen Platform (GRO), the Lauwerszee Trough High Pressures (LTHP), the Frisian Platform (FP) and the Lauwerszee Trough (LT). I have investigated which reservoir factors are most influential in deciding whether or not seismicity occurs. The stress ratio has proven to be the most critical parameter. Then, for the stress ratio, I have computed the stress ratio range for each region at which failure will occur. Above the stress ratio, seismic activity will occur, and below the stress ratio, no seismic activity will occur. To answer the research question "Can the reservoir properties of small gas fields in the Netherlands predict the occurrence of seismicity?", I have taken the following steps.
First, I have examined the probability of all small Dutch gas fields being responsible for a seismic event. Based on the distance between the gas field and the nearest event, as well as the presence of other fields in the surrounding area, I have derived a classification for the likelihood that the field was associated with induced seismicity. Second, I have run a sensitivity analysis to identify which parameter was most significant. I have accomplished this by implementing a semi-analytical model that computed and depicted depletion-induced stresses and fault slip along an inclined fault. The model calculated the depletion pressure at which seismic slip starts to occur, here called the onset pressure, based on reservoir data and fault characteristics. The reservoir data contains the compaction coefficient, critical slip weakening distance, dip angle, dynamic friction coefficient, initial reservoir pressure, Poisson's ratio, porosity, reservoir depth, reservoir thickness, shear modulus, static friction coefficient and stress ratio while the fault characteristics included the absolute fault offset and whether the fault is bounding or not.
Afterwards, I have plotted the onset pressure versus the relative fault offset and assessed the sensitivity of the onset pressure whilst changing input parameter settings, namely the critical slip weakening distance, dip angle, dynamic friction coefficient, initial reservoir pressure, Poisson's ratio, porosity, reservoir thickness, shear modulus, static friction and stress ratio. The most critical parameter has turned out to be the stress ratio. I have examined the stress ratio ranges for each field in order to assess whether this parameter could predict the occurrence of seismicity for an entire region. Some fields that do not suit the optimal regional stress ratio have been considered anomalies and investigated further. The main explanations for the anomalies have been geological complexity, assumed synthetic fault offsets, over- or underestimated offsets, unregistered seismic events and substantial overpressure.
The answer to the research question is, yes, it is possible to predict whether seismicity will occur in a small Dutch gas field located in the Rotliegend formation based on reservoir data and fault characteristics. A regional stress ratio has been determined for each of the five regions. The regional stress ratio is 0.51 for NHP, 0.58 for Groningen, 0.69 for LTHP, 0.46 and 0.47 for FP and 0.50 and 0.56 for LT. Salt layers have most likely contributed to higher regional stress ratios for GRO, LT and LTHP. ...
First, I have examined the probability of all small Dutch gas fields being responsible for a seismic event. Based on the distance between the gas field and the nearest event, as well as the presence of other fields in the surrounding area, I have derived a classification for the likelihood that the field was associated with induced seismicity. Second, I have run a sensitivity analysis to identify which parameter was most significant. I have accomplished this by implementing a semi-analytical model that computed and depicted depletion-induced stresses and fault slip along an inclined fault. The model calculated the depletion pressure at which seismic slip starts to occur, here called the onset pressure, based on reservoir data and fault characteristics. The reservoir data contains the compaction coefficient, critical slip weakening distance, dip angle, dynamic friction coefficient, initial reservoir pressure, Poisson's ratio, porosity, reservoir depth, reservoir thickness, shear modulus, static friction coefficient and stress ratio while the fault characteristics included the absolute fault offset and whether the fault is bounding or not.
Afterwards, I have plotted the onset pressure versus the relative fault offset and assessed the sensitivity of the onset pressure whilst changing input parameter settings, namely the critical slip weakening distance, dip angle, dynamic friction coefficient, initial reservoir pressure, Poisson's ratio, porosity, reservoir thickness, shear modulus, static friction and stress ratio. The most critical parameter has turned out to be the stress ratio. I have examined the stress ratio ranges for each field in order to assess whether this parameter could predict the occurrence of seismicity for an entire region. Some fields that do not suit the optimal regional stress ratio have been considered anomalies and investigated further. The main explanations for the anomalies have been geological complexity, assumed synthetic fault offsets, over- or underestimated offsets, unregistered seismic events and substantial overpressure.
The answer to the research question is, yes, it is possible to predict whether seismicity will occur in a small Dutch gas field located in the Rotliegend formation based on reservoir data and fault characteristics. A regional stress ratio has been determined for each of the five regions. The regional stress ratio is 0.51 for NHP, 0.58 for Groningen, 0.69 for LTHP, 0.46 and 0.47 for FP and 0.50 and 0.56 for LT. Salt layers have most likely contributed to higher regional stress ratios for GRO, LT and LTHP. ...
Using a field classification, I have assessed the likelihood that a gas field caused a seismic event. I have put the focus on all of the minor gas fields located in the Rotliegend sandstone formation in the Netherlands. These gas fields were divided into five geologically distinctly different regions: the North Holland Platform (NHP), the Groningen Platform (GRO), the Lauwerszee Trough High Pressures (LTHP), the Frisian Platform (FP) and the Lauwerszee Trough (LT). I have investigated which reservoir factors are most influential in deciding whether or not seismicity occurs. The stress ratio has proven to be the most critical parameter. Then, for the stress ratio, I have computed the stress ratio range for each region at which failure will occur. Above the stress ratio, seismic activity will occur, and below the stress ratio, no seismic activity will occur. To answer the research question "Can the reservoir properties of small gas fields in the Netherlands predict the occurrence of seismicity?", I have taken the following steps.
First, I have examined the probability of all small Dutch gas fields being responsible for a seismic event. Based on the distance between the gas field and the nearest event, as well as the presence of other fields in the surrounding area, I have derived a classification for the likelihood that the field was associated with induced seismicity. Second, I have run a sensitivity analysis to identify which parameter was most significant. I have accomplished this by implementing a semi-analytical model that computed and depicted depletion-induced stresses and fault slip along an inclined fault. The model calculated the depletion pressure at which seismic slip starts to occur, here called the onset pressure, based on reservoir data and fault characteristics. The reservoir data contains the compaction coefficient, critical slip weakening distance, dip angle, dynamic friction coefficient, initial reservoir pressure, Poisson's ratio, porosity, reservoir depth, reservoir thickness, shear modulus, static friction coefficient and stress ratio while the fault characteristics included the absolute fault offset and whether the fault is bounding or not.
Afterwards, I have plotted the onset pressure versus the relative fault offset and assessed the sensitivity of the onset pressure whilst changing input parameter settings, namely the critical slip weakening distance, dip angle, dynamic friction coefficient, initial reservoir pressure, Poisson's ratio, porosity, reservoir thickness, shear modulus, static friction and stress ratio. The most critical parameter has turned out to be the stress ratio. I have examined the stress ratio ranges for each field in order to assess whether this parameter could predict the occurrence of seismicity for an entire region. Some fields that do not suit the optimal regional stress ratio have been considered anomalies and investigated further. The main explanations for the anomalies have been geological complexity, assumed synthetic fault offsets, over- or underestimated offsets, unregistered seismic events and substantial overpressure.
The answer to the research question is, yes, it is possible to predict whether seismicity will occur in a small Dutch gas field located in the Rotliegend formation based on reservoir data and fault characteristics. A regional stress ratio has been determined for each of the five regions. The regional stress ratio is 0.51 for NHP, 0.58 for Groningen, 0.69 for LTHP, 0.46 and 0.47 for FP and 0.50 and 0.56 for LT. Salt layers have most likely contributed to higher regional stress ratios for GRO, LT and LTHP.
First, I have examined the probability of all small Dutch gas fields being responsible for a seismic event. Based on the distance between the gas field and the nearest event, as well as the presence of other fields in the surrounding area, I have derived a classification for the likelihood that the field was associated with induced seismicity. Second, I have run a sensitivity analysis to identify which parameter was most significant. I have accomplished this by implementing a semi-analytical model that computed and depicted depletion-induced stresses and fault slip along an inclined fault. The model calculated the depletion pressure at which seismic slip starts to occur, here called the onset pressure, based on reservoir data and fault characteristics. The reservoir data contains the compaction coefficient, critical slip weakening distance, dip angle, dynamic friction coefficient, initial reservoir pressure, Poisson's ratio, porosity, reservoir depth, reservoir thickness, shear modulus, static friction coefficient and stress ratio while the fault characteristics included the absolute fault offset and whether the fault is bounding or not.
Afterwards, I have plotted the onset pressure versus the relative fault offset and assessed the sensitivity of the onset pressure whilst changing input parameter settings, namely the critical slip weakening distance, dip angle, dynamic friction coefficient, initial reservoir pressure, Poisson's ratio, porosity, reservoir thickness, shear modulus, static friction and stress ratio. The most critical parameter has turned out to be the stress ratio. I have examined the stress ratio ranges for each field in order to assess whether this parameter could predict the occurrence of seismicity for an entire region. Some fields that do not suit the optimal regional stress ratio have been considered anomalies and investigated further. The main explanations for the anomalies have been geological complexity, assumed synthetic fault offsets, over- or underestimated offsets, unregistered seismic events and substantial overpressure.
The answer to the research question is, yes, it is possible to predict whether seismicity will occur in a small Dutch gas field located in the Rotliegend formation based on reservoir data and fault characteristics. A regional stress ratio has been determined for each of the five regions. The regional stress ratio is 0.51 for NHP, 0.58 for Groningen, 0.69 for LTHP, 0.46 and 0.47 for FP and 0.50 and 0.56 for LT. Salt layers have most likely contributed to higher regional stress ratios for GRO, LT and LTHP.
In total 326 terpen in the Netherlands are classified as national monuments. A large portion of the terpen are located in the province Groningen. Groningen is often in the news, because of the earthquakes that took place, which were caused by the gas-extraction activities. The earthquakes caused damage to infrastructure and they can also be a threat to the stability of the terpen. Since the earthquakes can lead to soil liquefaction. The goal of this report is to investigate the risk of liquefaction to the terpen due to induced earthquakes. Furthermore, fine sands was the most liquefiable soil type. The Naaldwijk and Eem formations have the highest liquefaction potential based on their soil compositions, densities and age. The Naaldwijk formation is the most prone to liquefaction since it is located more shallow in the underground. Afterwards, cone penetration test data was used to evaluate the soil classes, soil unit weights and soil behaviour indexes. The soil behaviour index values were used to asses the liquefaction potential. In the end, none of the three chosen terpen were liquefiable. Moreover, 2D and 3D visualizations were made in order to better understand the heights and slopes of the terpen.
...
In total 326 terpen in the Netherlands are classified as national monuments. A large portion of the terpen are located in the province Groningen. Groningen is often in the news, because of the earthquakes that took place, which were caused by the gas-extraction activities. The earthquakes caused damage to infrastructure and they can also be a threat to the stability of the terpen. Since the earthquakes can lead to soil liquefaction. The goal of this report is to investigate the risk of liquefaction to the terpen due to induced earthquakes. Furthermore, fine sands was the most liquefiable soil type. The Naaldwijk and Eem formations have the highest liquefaction potential based on their soil compositions, densities and age. The Naaldwijk formation is the most prone to liquefaction since it is located more shallow in the underground. Afterwards, cone penetration test data was used to evaluate the soil classes, soil unit weights and soil behaviour indexes. The soil behaviour index values were used to asses the liquefaction potential. In the end, none of the three chosen terpen were liquefiable. Moreover, 2D and 3D visualizations were made in order to better understand the heights and slopes of the terpen.