<p>Reservoir properties are mainly determined based on well log information. However, wells in most reservoirs are sparse and widely spread compared to the size of the reservoir. Seismic data is thus one of the most important complementary sources of information used to build 3D models of hydrocarbon reservoirs. The need for a high quality reservoir description starts as soon as a discovery is made. In the appraisal phase, hydrocarbons in place and the amount of recoverable reserves are estimated based on the reservoir model. Improved structural models are also needed in optimal well placement during the production and development phase of a reservoir. Knowledge about saturation and pressure distributions in a reservoir are valuable both in the exploration and development phase of a reservoir. This knowledge is used to evaluate the size of a field, determine an optimal drainage pattern, and decide on optimal well design to reduce risks for blow-outs and damage on production equipment. Reducing uncertainty in reservoir property estimates from seismic data have large economic impact on the development of a hydrocarbon reservoir.</p><p>Quantitative reservoir property information can be obtained either through direct estimates of reservoir properties from seismic data or through estimates of elastic properties (velocities and densities) that are related to reservoir properties. The relationship between physical properties of rocks and fluids and P-wave seismic data are often empirical and non-unique. This leads to large uncertainties in reservoir models derived from pressure wave seismic data alone. Since shear waves do not propagate through fluids, combined use of pressure wave seismic data and shear wave seismic data might increase our ability to derive fluid and lithology properties from seismic data. One way to obtain information about shear wave velocities over a large area is to acquire multicomponent seismic data (for instance x, y, and z component geophone data). Parts of this thesis focus on methods to combine the information from multicomponent seismic data with pressure wave (hydrophone) seismic data. In this way we improve the accuracy in the estimates of pressure wave velocity, shear wave velocity and density in the subsurface.</p><p>To obtain information about changes in reservoir parameters like fluid saturation and pore pressure during production, comparisons between different vintages of seismic data acquired over the field can be performed. Differences in the seismic signal from the same area over a time period (time-lapse seismic data) can be interpreted as changes in reservoir properties. Benefits of improved reservoir characterization include ability to locate bypassed oil and mapping of fluid fronts. This leads to saved costs due to reduced number of misplaced wells, and increased production because of optimized well placement. In the early days of seismic reservoir monitoring, the analyses were qualitative, e.g. to identify undrained areas, analyzing the sealing capacity of faults, and detect drainage patterns. Today, time-lapse seismic analysis is still mainly qualitative. To be able to obtain more quantitative estimates of changes in reservoir properties from the time-lapse seismic data, we need to establish links between the rock parameters and the seismic data. I have used both time-lapse surface seismic data and time-lapse multicomponent seismic data to estimate production related changes in fluid saturation and pressure.</p><p>Finally, to be able to utilize rock physical information obtained from seismic reservoir characterization in reservoir modelling, information about uncertainties in the estimates are essential. One way to do this is to use deterministic models (rock physics models) that relates reservoir properties to seismic data, and assume that the model parameters are independent. However, the variables in these estimations are inherently dependent and should be treated as such. By formulating the problem in a Bayesian framework, dependencies between the different variables and spatial dependencies can easily be included. I have used both deterministic uncertainty analysis and Bayesian estimation methods to quantify uncertainties in the estimates.</p>

Reservoir properties are mainly determined based on well log information. However, wells in most reservoirs are sparse and widely spread compared to the size of the reservoir. Seismic data is thus one of the most important complementary sources of information used to build 3D models of hydrocarbon reservoirs. The need for a high quality reservoir description starts as soon as a discovery is made. In the appraisal phase, hydrocarbons in place and the amount of recoverable reserves are estimated based on the reservoir model. Improved structural models are also needed in optimal well placement during the production and development phase of a reservoir. Knowledge about saturation and pressure distributions in a reservoir are valuable both in the exploration and development phase of a reservoir. This knowledge is used to evaluate the size of a field, determine an optimal drainage pattern, and decide on optimal well design to reduce risks for blow-outs and damage on production equipment. Reducing uncertainty in reservoir property estimates from seismic data have large economic impact on the development of a hydrocarbon reservoir. Quantitative reservoir property information can be obtained either through direct estimates of reservoir properties from seismic data or through estimates of elastic properties (velocities and densities) that are related to reservoir properties. The relationship between physical properties of rocks and fluids and P-wave seismic data are often empirical and non-unique. This leads to large uncertainties in reservoir models derived from pressure wave seismic data alone. Since shear waves do not propagate through fluids, combined use of pressure wave seismic data and shear wave seismic data might increase our ability to derive fluid and lithology properties from seismic data. One way to obtain information about shear wave velocities over a large area is to acquire multicomponent seismic data (for instance x, y, and z component geophone data). Parts of this thesis focus on methods to combine the information from multicomponent seismic data with pressure wave (hydrophone) seismic data. In this way we improve the accuracy in the estimates of pressure wave velocity, shear wave velocity and density in the subsurface. To obtain information about changes in reservoir parameters like fluid saturation and pore pressure during production, comparisons between different vintages of seismic data acquired over the field can be performed. Differences in the seismic signal from the same area over a time period (time-lapse seismic data) can be interpreted as changes in reservoir properties. Benefits of improved reservoir characterization include ability to locate bypassed oil and mapping of fluid fronts. This leads to saved costs due to reduced number of misplaced wells, and increased production because of optimized well placement. In the early days of seismic reservoir monitoring, the analyses were qualitative, e.g. to identify undrained areas, analyzing the sealing capacity of faults, and detect drainage patterns. Today, time-lapse seismic analysis is still mainly qualitative. To be able to obtain more quantitative estimates of changes in reservoir properties from the time-lapse seismic data, we need to establish links between the rock parameters and the seismic data. I have used both time-lapse surface seismic data and time-lapse multicomponent seismic data to estimate production related changes in fluid saturation and pressure. Finally, to be able to utilize rock physical information obtained from seismic reservoir characterization in reservoir modelling, information about uncertainties in the estimates are essential. One way to do this is to use deterministic models (rock physics models) that relates reservoir properties to seismic data, and assume that the model parameters are independent. However, the variables in these estimations are inherently dependent and should be treated as such. By formulating the problem in a Bayesian framework, dependencies between the different variables and spatial dependencies can easily be included. I have used both deterministic uncertainty analysis and Bayesian estimation methods to quantify uncertainties in the estimates.

Earthquake catalogues are usually dominated by diffusive behaviour consistent with the Omori law of aftershocks. This is investigated in terms of waiting times, i.e. the time between successive events in a time-sorted earthquake catalogue. The theoretical waiting time probability distribution for the Omori law is derived and shown to predict the numerically produced Omori aftershock sequence well. These results enhance our understanding of aftershock processes and demonstrate that previous waiting time interpretations were severely flawed. Iceland earthquake catalogues are studied in terms of waiting times. Omori aftershock sequences are shown to predict most datasets well but there are some significant exceptions. One of these is data from the glacier covered Katla volcano in South Iceland, with few aftershocks. This dataset can be further split into two geographical groups: Several hundred volcano-tectonic earthquakes occurring within the caldera, reaching depths down to 15 km, and thousands of emergent low frequency earthquakes with a poorly defined shallow source in Goðabunga, in the western part of Katla. These events are investigated further. The lp events at Goðabunga have been recorded for decades and show a clear seasonal and climate-related correlation where their number increases in the autumn as well as during warmer years. Many of them form groups with very with similar waveforms. New broad-band seismic data suggests that the lp events originate in a steep outlet glacier covering Katla. Here, ice movement leads to ice falls over the steep escarpment, and we now believe that the lp events are generated by large ice falls rather than being related to gas or magma movements within the volcano, and are not precursors to an eruption as previously suspected. This observation probably has major significance for hazard estimation at the many ice-covered volcanoes around the world. We report near-field (vlp) signals simultaneous with the largest lp events. Our data is partly consistent in character with surface deformation (displacement and tilt) due to the ice movements. However, in line with results from elsewhere, the magnitudes of the observed effects are large relative to those from mathematical modelling. Our analysis suggests that the signal is not an instrumental artefact. Possible explanations are discussed.

The knowledge of the geology of the sedimentary basins from the Gulf of Panama is still quite limited. There is a lack of data from the basin geometry, the thickness, the continuity and connection between the basins, and from the characteristics of the crystalline basement rocks beneath the sedimentary basins. Geological maps have been published without evidence from geophysical studies; i.e. marine faults patters are showed only as the continuation of fault pattern on land and in some cases faults are showed only to adjust geodynamics models. In the marines areas the geophysical surveys so far carried out, like seismic reflection and well logging, have not given information about the nature of and depth to the crystalline basement rock and interpretations of aeromagnetic and gravity data are still missing. Many of the geophysical surveys like aeromagnetic and marine gravity data have been published as contour maps. However, different data processing techniques and various references levels have been used, which do not permit an integral regional analysis. Here we present composite regional aeromagnetic and gravity maps and integral interpretations with reference to source parameters such as; depths to the top of basement rock, faults patters, locations of magnetic boundaries, susceptibility contrasts, geometry and connection between the basins. The interpretations are based on regional aeromagnetic maps and on marine and land gravity data compiled from several sources and integrated with reference to a fixed level. Various techniques have been applied for the interpretation e.g. enhancement of the aeromagnetic anomalies maps by sun shading technique, applying band pass filtering and upward analytic continuation. Maps have also been transformed into images called 3D analytic signal amplitude and local wave number maps. The depth estimates resulting from the analyses of these maps are compared and the location of interpreted contacts are combined into a map showing the dip direction for contacts. The Bouguer gravity data from the Gulf of Panama are transformed into a residual anomaly map using a filtering technique. This residual anomaly map have been analyzed in order to estimate depths to the top of the basement rocks. / <p>Godkänd; 2008; 20080602 (ysko)</p>

The tensor radio-magnetotelluric (RMT) method has extensively been used in near-surface investigations to obtain resistivity models of the subsurface. The main objective of this thesis is to further develop the RMT survey technique for a less paid attention and challenging environment namely on shallow water bodies and in the urban environment. The other objective is to develop a new processing technique to enhance the resolution and sensitivity of the tensor RMT method. For the first time a data acquisition system called ‘boat-towed RMT’ is introduced that has the capability to measure tensor RMT data on water bodies like lakes and rivers. A RMT survey carried out on Lake Mälaren near the city of Stockholm shows the capability and efficiency of the boat-towed RMT system. The resistivity models obtained from the RMT data are consistent from one line to another and show good correlation with the existing geological and drill core data. In general, a three-layer resistivity model was obtained that has a conductive layer interpreted as lake sediments, which is sandwiched between high resistive bedrock and resistive water column. A coherent discontinuity of low resistivity zone was observed in bedrock across all the lines. It was interpreted to originate from a major fracture zone striking in the direction of water bodies. However, due to the lack of penetration, RMT method alone was insufficient to provide a conclusive interpretation of this. Synthetic analysis was performed and showed that lower frequencies using controlled-sources are required to obtain the desired penetration depth. We took the advantage of the Swedish winters and carried out controlled-source RMT measurements on frozen lake at the same location. The new controlled-source models have enough depth penetration to delineate fractured bedrock. Furthermore, in order to improve the resolution and sensitivity of tensor RMT data, a new processing technique was developed that preserves the identity of each transmitter and allows improved resistivity model of the subsurface. These new acquisition and processing techniques should be useful in many different applications for urban infrastructure planning projects especially in Scandinavia where 7% of the land is covered by fresh water bodies and is poorly explored for these purposes.

digitalisering@umu.se

This thesis presents applications of geophysical methods in the fields of environment and hydrogeology. In relation to environmental problems, two different geophysical surveys have been carried out; one to study an arsenic contaminated area in the southern Thailand (paper I) and a second to locate shallow faults in Quaternary sediments in an area around the Ongkharak Nuclear Research Centre, central Thailand (paper II). For hydro-geological problems, surveys were conducted in southern Sweden (paper III) and in the Vientiane basin, Laos (paper IV). In the arsenic contaminated area, tin and associated minerals, i.e. arsenopyrite and pyrite, have been extracted from granites and natural processes and the mining activities led to arsenic contamination in the environment. Electrical resistivity and self potential (SP) have been used to define the distribution of arsenic contamination in the groundwater. Resistivities of 25 - 100 ohm-m and a positive SP anomaly of 66.0 mV were observed in an area where the arsenic content in auger water at 3.5 to 5.0 m depths was high, 0.5 - 5.0 mg/l. Integrated interpretation of resistivity, seismic refraction, GPR, and gravity data gave a clear image of subsurface structures at a depth to 30 m. There was a good correlation between the resistivity and the gravity data. A subsurface rise was found, which possibly acts as a naturally buried dam, separating a high contaminated area from a low contaminated area. This study has demonstrated that the combination of geophysical methods is successful in delineating contaminated areas and contributes to the understanding of a possible mechanism for the distribution of arsenic. In the Ongkharak Nuclear Research Centre area combined GPR and resistivity pseudosections (dipole-dipole and pole-pole arrays) have given a good image of shallow faults in Quaternary sediments, faults that were originally indicated from regional remote sensing interpretations. Horizontal discontinuities of reflected signals obtained by GPR and images of lateral resistivity variation have been correlated to faults or subsurface movement identified by geological mapping in trenches. This signature of the faults is caused by contrasts in dielectric permittivity and/or in resistivity, which originates from vertical displacement at sedimentary layers and from sediments filling the faults. The positions of sub-faults as identified by GPR and their strike directions obtained from the trenching data (N60°W - N70°W, N65°W - N70°W, and N30°W) agree with the general NW-SE trend of the major faults, the Mae Ping Fault Zone, the Nakhon Nayok-Prachinburi and the Ongkharak faults in central Thailand. Thermoluminescence (TL) dating showed that sub-faults in the area have been active at about 7,500-2,400, 4,800- 1,750, and 9,700-2,300 years ago. Thus, these sub-faults have been classified to be of the same generation and they are defined as "capable faults" with reference to the criteria of U.S. Nuclear Regulatory Commission. Magnetic Resonance Sounding (MRS) has been successfully tested for detecting groundwater and in combination with Vertical Electrical Sounding to characterizing aquifer in southern Sweden and in the Vientiane basin, Laos. The combination of MRS and VES in the southern areas of Sweden shows that low resistivity layers interpreted as clay are sometimes identified close to the surface. The results here have shown that the MRS signals penetrate through the clay and that deeper aquifer can still be detected. The MRS data suggest aquifers that are not only hosted in soft sediment materials (moraine, sand, and mixed materials), but also hosted in basement rocks. Based on the MRS and borehole pumping test data, the hydraulic conductivity of aquifers has been estimated and the results agree with yield, average water content and subsurface geological data. The results from the measurement in the Vientiane basin have shown that there is usually two - three water bearing layers, and the "best aquifer" is found at depths between 15 and 25 m, with regard to high water content, permeability and resistivities indicating fresh water. MRS has also shown to be an important tool in constraining layer thickness and distinguishing low resistive layers of impermeable rock from what could have been interpreted as water in the VES interpretation. MRS data also suggest a clay layer at depths between 30 and 50 m, which is overlying halite deposits. This clay layer may act as a naturally sealing layer to protect the fresh water in above aquifer from salt contamination. On the basis of this drilling for fresh water is recommended not to penetrate deeper than 20 to 40 m, depending of the local depth to the clay layer. / Godkänd; 2007; 20071126 (ysko)

No description available.

<p>Godkänd; 1997; 20070418 (ysko)</p>

Ground Penetrating Radar is a widely used technique for detecting objects in the subsurface. However, the objects typically appear as hyperbolic curves in the raw data's time domain. Therefore, the size and the location of the objects are hard to interpret from the raw data. Migration is a helpful technique to determine the subsurface velocity and to transform the raw data into an image where the object's size and location are easier to interpret. In this thesis, we discuss a strategy for automatic migration. We apply the automatic strategy with a few standard migration methods, Kirchhoff, Phase-shift, and f-k Stretch migration. The automatic strategy was tested on both real and synthetic data. The results showed that the automatic migration strategy successfully could improve the interpretation of both datasets. In the synthetic data test, we could estimate the location of objects with a relative error of about 2-12%.