With the advancements in acquisition and processing of seismic reflection data recorded over crystalline rocks, building three-dimensional geologic models becomes increasingly favorable. Because of little available petrophysical data, interpretations of seismic reflection data in hardrock terrains are often speculative. Potential field data modeling are sometimes performed in order to reduce the ambiguity of seismic reflection interpretations. The Kristineberg mining area in the western part of the Paleoproterozoic Skellefte Ore District was chosen to construct a pilot three-dimensional geologic model in an attempt to understand the crustal architecture in the region and how the major mineral systems operated in this architecture. To contribute to this aim, two parallel seismic reflection profiles were acquired in 2003 and processed to 20 sec with special attention to the top 4 sec of data. Several reflections were imaged and interpreted by the aid of reflector modeling, borehole data, 2.5D and 3D potential field modeling, and geological observations. Interpretations are informative at the crustal scale and help to construct a three-dimensional geologic model of the Kristineberg mining area. The three-dimensional geologic model covers an area of 30×30 km2 down to a depth of 12 km. The integrations help to interpret a structural basement to the Skellefte volcanic rocks, possibly with Bothnian Basin metasedimentary affinity. The contact is a shear-zone that separates the two units, generating large fold structures, which can be observed in the region. The interpretations help to divide the Revsund granitic rocks into two major groups based on their present shape and thickness. A large gravity low in the south is best represented by the intrusion of thick dome of Revsund granite. In the north, the low-gravity corresponds to the intrusion of sheet-like Revsund granites. In general, the structure associated with the Skellefte volcanics and the overlying metasedimentary rocks are two thrusts exposing the Skellefte volcanic rocks in the cores of hanging wall anticlinal structures. Lack of coherent reflectivity in the seismic reflection data may be due to complex faulting and folding systems observed in the Skellefte volcanics. Ultramafic sills within the metasedimentary rocks are interpreted to extend down to depths of about 5-6 km. The interpretations are helpful for targeting new VHMS deposits and areas with gold potential. For VHMS deposits, these are situated in the southern limb of a local synformal structure south of the Kristineberg mine, on the contact between the Revsund granite and the Skellefte volcanic rocks. A combination of metasedimentary and mafic-ultramafic rocks are highly gold prospective in the west, similar to observations elsewhere in the region. There are still questions that remain unanswered and need more work. New data in the study area will help to answer questions related to e.g., an enigmatic diffraction seismic signal in Profile 5 and the structural relationship between the Skellefte volcanic rocks and the Malå volcanics. Although the derived 3D geologic model is preliminary and constructed at the crustal scale, it provides useful information to better understand the tectonic evolution of the Kristineberg mining area.

Antes de se fazer uma estimativa ou uma simulação geoestatística, os domínios geológicos devem ser modelados de forma que cada domínio utilize apenas dados que pertencem a ele. Na industria mineral a incerteza oriunda dos teores geralmente é levada em consideração, entretanto a incerteza gerada pelo modelo nem sempre é analisada. Sabendo que a maior fonte de incerteza está na transição de uma litologia para outra, essa dissertação visa avaliar a incerteza do modelo geológico através de simulações de funções distâncias assinaladas em zonas de maior incerteza, gerando vários modelos com diferentes proporções de cada litologias. Um estudo de caso em um banco de dados real com alta complexidade geológica é utilizado para avaliar o uso da metodologia. O método se mostrou eficaz para avaliar o impacto da diferença de volume que cada litologia pode alcançar, demonstrando a importância de medir a incerteza na construção de modelos geológicos. / Before making an estimation or a geostatistical simulation, geological domains must be modeled so that each domain uses only data that belongs to it. In the mineral industry the uncertainty derived from the grades is generally taken into account, however the uncertainty generated by the model is not always analyzed. Knowing that the greatest source of uncertainty is in the transition from one lithology to another, this dissertation aims to evaluate the uncertainty of the geological model through signed distances function simulation in uncertainty zones, generating several models with different proportions of each lithology. A case study in a real dataset with high geological complexity is used to evaluate the use of the methodology. The method proved effective in assessing the impact of the volume difference that each lithology can reach, demonstrating the importance of measuring uncertainty in the construction of geological models.

<p>With the advancements in acquisition and processing of seismic reflection data recorded over crystalline rocks, building three-dimensional geologic models becomes increasingly favorable. Because of little available petrophysical data, interpretations of seismic reflection data in hardrock terrains are often speculative. Potential field data modeling are sometimes performed in order to reduce the ambiguity of seismic reflection interpretations. The Kristineberg mining area in the western part of the Paleoproterozoic Skellefte Ore District was chosen to construct a pilot three-dimensional geologic model in an attempt to understand the crustal architecture in the region and how the major mineral systems operated in this architecture. To contribute to this aim, two parallel seismic reflection profiles were acquired in 2003 and processed to 20 sec with special attention to the top 4 sec of data. Several reflections were imaged and interpreted by the aid of reflector modeling, borehole data, 2.5D and 3D potential field modeling, and geological observations. Interpretations are informative at the crustal scale and help to construct a three-dimensional geologic model of the Kristineberg mining area. The three-dimensional geologic model covers an area of 30×30 km² down to a depth of 12 km. The integrations help to interpret a structural basement to the Skellefte volcanic rocks, possibly with Bothnian Basin metasedimentary affinity. The contact is a shear-zone that separates the two units, generating large fold structures, which can be observed in the region. The interpretations help to divide the Revsund granitic rocks into two major groups based on their present shape and thickness. A large gravity low in the south is best represented by the intrusion of thick dome of Revsund granite. In the north, the low-gravity corresponds to the intrusion of sheet-like Revsund granites. In general, the structure associated with the Skellefte volcanics and the overlying metasedimentary rocks are two thrusts exposing the Skellefte volcanic rocks in the cores of hanging wall anticlinal structures. Lack of coherent reflectivity in the seismic reflection data may be due to complex faulting and folding systems observed in the Skellefte volcanics. Ultramafic sills within the metasedimentary rocks are interpreted to extend down to depths of about 5-6 km. The interpretations are helpful for targeting new VHMS deposits and areas with gold potential. For VHMS deposits, these are situated in the southern limb of a local synformal structure south of the Kristineberg mine, on the contact between the Revsund granite and the Skellefte volcanic rocks. A combination of metasedimentary and mafic-ultramafic rocks are highly gold prospective in the west, similar to observations elsewhere in the region. There are still questions that remain unanswered and need more work. New data in the study area will help to answer questions related to e.g., an enigmatic diffraction seismic signal in Profile 5 and the structural relationship between the Skellefte volcanic rocks and the Malå volcanics. Although the derived 3D geologic model is preliminary and constructed at the crustal scale, it provides useful information to better understand the tectonic evolution of the Kristineberg mining area. </p>

Rapid economic evaluations of investment alternatives in the oil and gas industry are typically contingent on fast and credible evaluations of reservoir models to make future forecasts. It is often important to also quantify inherent risks and uncertainties in these evaluations. These ideally require several full-scale numerical simulations which is time consuming, impractical, if not impossible to do with conventional (Finite Difference) simulators in real life situations. In this research, the aim will be to improve on the efficiencies associated with these tasks. This involved exploring the applications of Fast Marching Methods (FMM) in both conventional and unconventional reservoir characterization problems. In this work, we first applied the FMM for rapidly ranking multiple equi-probable geologic models. We demonstrated the suitability of drainage volume, efficiently calculated using FMM, as a surrogate parameter for field-wide cumulative oil production (FOPT). The probability distribution function (PDF) of the surrogate parameter was point-discretized to obtain 3 representative models for full simulations. Using the results from the simulations, the PDF of the reservoir performance parameter was constructed. Also, we investigated the applicability of a higher-order-moment-preserving approach which resulted in better uncertainty quantification over the traditional model selection methods. Next we applied the FMM for a hydraulically fractured tight oil reservoir model calibration problem. We specifically applied the FMM geometric pressure approximation as a proxy for rapidly evaluating model proposals in a two-stage Markov Chain Monte Carlo (MCMC) algorithm. Here, we demonstrated the FMM-based proxy as a suitable proxy for evaluating model proposals. We obtained results showing a significant improvement in the efficiency compared to conventional single stage MCMC algorithm. Also in this work, we investigated the possibility of enhancing the computational efficiency for calculating the pressure field for both conventional and unconventional reservoirs using FMM. Good approximations of the steady state pressure distributions were obtained for homogeneous conventional waterflood systems. In unconventional system, we also recorded slight improvement in computational efficiency using FMM pressure approximations as initial guess in pressure solvers.

Antes de se fazer uma estimativa ou uma simulação geoestatística, os domínios geológicos devem ser modelados de forma que cada domínio utilize apenas dados que pertencem a ele. Na industria mineral a incerteza oriunda dos teores geralmente é levada em consideração, entretanto a incerteza gerada pelo modelo nem sempre é analisada. Sabendo que a maior fonte de incerteza está na transição de uma litologia para outra, essa dissertação visa avaliar a incerteza do modelo geológico através de simulações de funções distâncias assinaladas em zonas de maior incerteza, gerando vários modelos com diferentes proporções de cada litologias. Um estudo de caso em um banco de dados real com alta complexidade geológica é utilizado para avaliar o uso da metodologia. O método se mostrou eficaz para avaliar o impacto da diferença de volume que cada litologia pode alcançar, demonstrando a importância de medir a incerteza na construção de modelos geológicos. / Before making an estimation or a geostatistical simulation, geological domains must be modeled so that each domain uses only data that belongs to it. In the mineral industry the uncertainty derived from the grades is generally taken into account, however the uncertainty generated by the model is not always analyzed. Knowing that the greatest source of uncertainty is in the transition from one lithology to another, this dissertation aims to evaluate the uncertainty of the geological model through signed distances function simulation in uncertainty zones, generating several models with different proportions of each lithology. A case study in a real dataset with high geological complexity is used to evaluate the use of the methodology. The method proved effective in assessing the impact of the volume difference that each lithology can reach, demonstrating the importance of measuring uncertainty in the construction of geological models.

Antes de se fazer uma estimativa ou uma simulação geoestatística, os domínios geológicos devem ser modelados de forma que cada domínio utilize apenas dados que pertencem a ele. Na industria mineral a incerteza oriunda dos teores geralmente é levada em consideração, entretanto a incerteza gerada pelo modelo nem sempre é analisada. Sabendo que a maior fonte de incerteza está na transição de uma litologia para outra, essa dissertação visa avaliar a incerteza do modelo geológico através de simulações de funções distâncias assinaladas em zonas de maior incerteza, gerando vários modelos com diferentes proporções de cada litologias. Um estudo de caso em um banco de dados real com alta complexidade geológica é utilizado para avaliar o uso da metodologia. O método se mostrou eficaz para avaliar o impacto da diferença de volume que cada litologia pode alcançar, demonstrando a importância de medir a incerteza na construção de modelos geológicos. / Before making an estimation or a geostatistical simulation, geological domains must be modeled so that each domain uses only data that belongs to it. In the mineral industry the uncertainty derived from the grades is generally taken into account, however the uncertainty generated by the model is not always analyzed. Knowing that the greatest source of uncertainty is in the transition from one lithology to another, this dissertation aims to evaluate the uncertainty of the geological model through signed distances function simulation in uncertainty zones, generating several models with different proportions of each lithology. A case study in a real dataset with high geological complexity is used to evaluate the use of the methodology. The method proved effective in assessing the impact of the volume difference that each lithology can reach, demonstrating the importance of measuring uncertainty in the construction of geological models.