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Undershultz, Jim (University of Queensland) | Mukherjee, Saswata (University of Queensland) | Wolhuter, Alexandra (University of Queensland) | Xu, Huan (China University of Petroleum, East China and The University of Queensland) | Banks, Eddie (Flinders University) | Noorduijn, Saskia (Flinders University) | McCallum, Jim (University of Western Australia)
There is an increasing need to understand the influence of faults in both gas production performance and the resulting potential impact on adjacent groundwater resources.Faults can exhibit a wide variety of hydraulic properties. Where resource development induces changes in pore pressure, the effective stress and thus the permeability can be transient. In this study, w explored strategies for characterizing fault zone properties for the initial purpose of evaluating gas production performance. The same fault characterization can then be incorporated into regional groundwater flow models to more accurately represent stress, strain and the resulting transmissivities when assessing the impact of gas development on adjacent aquifers. Conventional fault zone analysis (juxtaposition, fault gouge or shale smear, fault reactivation) is combined with hydrodynamic analysis (distribution of hydraulic head and hydrochemistry) and surface water hydrology and hydrochemistry to evaluate across fault or up fault locations of enhanced hydraulic conductivity at specific locations of complex fault systems. The locations of identified vertical hydraulic communication from the hydraulic analysis are compared with the fault zone architecture derived from the 3D seismic volume overlain with the in-situ stress characterization. This provides an independent method of assessing other potential hydraulic communication locations based on seismic alone where no other hydraulic or hydrochemical information is available. A groundwater model is used in an inverse approach to assess the hydraulic properties required to generate observed hydrochemical anomalies so that a realistic range of rock properties can be assigned throughout the geological model to other faults. We use a case study example of the Gloucester Basin in New South Wales in eastern Australia to demonstrate how some of these techniques can be applied. The Gloucester Basin has been subject to exploration of coal seam gas with some pilot testing but no commercial production. It also contains data from groundwater monitoring bores and surface water features. The methodologies described can be applied elsewhere when faults play a key role in determining gas production performance or characterisation of groundwater flow system hydraulics in gas development areas.
Bannister, Michele T. (Department of Physics and Astronomy, University of Canterbury, Christchurch, NZ, and Astrophysics Research Centre, School of Mathematics & Physics, Queens University Belfast, UK) | Nobes, David (Department of Geophysics, East China University of Technology, Nanchang 330013, Jiangxi, China) | Sletten, Ronald S. (Department of Earth and Space Sciences, University of Washington, Seattle, Washington 98195, USA) | Godfrey, Myfanwy J. (Raine Associates, Level 23, 127 Creek Street, Brisbane, Queensland 4000, Australia) | Cottrell, Peter (Department of Physics and Astronomy, University of Canterbury, Christchurch, NZ)
ABSTRACT Subsurface studies of the arid periglacial geomorphology of the McMurdo Dry Valleys of Antarctica are limited. Electromagnetic imaging in this polar desert is challenging, due to the high ionic content of the water in the near-surface active layer. We present time-domain electromagnetic (TEM) data from our near-surface geophysical investigations of the polygonal patterned ground in Victoria Valley. The data quality is highly variable, and individual sites yielded noisy data; however, the results are generally consistent across the site. Our modelling suggests a thin, highly conductive layer at a depth of 140 to 170 m across half a kilometer of the valley, near Lake Victoria, which could be due to unfrozen brackish water in soil at depth. Presentation Date: Monday, September 16, 2019 Session Start Time: 1:50 PM Presentation Start Time: 4:20 PM Location: 303B Presentation Type: Oral
Bannister, Michele T. (Astrophysics Research Centre, School of Mathematics & Physics, Queen's University Belfast, Northern Ireland, UK) | Nobes, David C. (Department of Geophysics, East China University of Technology, Nanchang, Jiangxi 330013, China) | Godfrey, Myfanwy J. (Raine & Associates, Level 23, 127 Creek Street, Brisbane, Queensland 4000, Australia) | Sletten, Ronald S. (Department of Earth Sciences, University of Washington, Seattle, Washington, USA)
ABSTRACT Electrical imaging in the McMurdo Dry Valleys of Antarctica is made difficult by the high contact resistance in the dry resistive soil at the surface. The project was successful in obtaining a long line of electrical resistivity imaging (ERI) data in Victoria Valley, as well as complementary ground penetrating radar (GPR) imaging. The ERI data have a large dynamic range, and are best viewed using two different scales: one to emphasize the highly resistive materials at depth, and the other to highlight the less resistive near-surface active layer. Of particular interest is a set of highly resistive near-surface bodies, one of which correlates with a strong reflection event in the GPR. The results are consistent with buried massive ice (BMI) that may be remnants from the last time the valley was filled with glacier ice. Presentation Date: Tuesday, September 17, 2019 Session Start Time: 1:50 PM Presentation Time: 1:50 PM Location: 217C Presentation Type: Oral
Niri, M. Emami (Institute of Petroleum Engineering of University of Tehran and Centre for Energy Geoscience, University of Western Australia) | Lumley, D. E. (Centre for Energy Geoscience, School of Physics, School of Earth Sciences, University of Western Australia)
Summary We present a new method for seismic reservoir characterization and reservoir-property modeling on the basis of an integrated analysis of 3D-seismic data and hydraulic flow units, and apply it to an example of a producing reservoir offshore Western Australia. Our method combines hydraulic-unit analysis with a set of techniques for seismic reservoir characterization including rock-physics analysis, Bayesian inference, prestack seismic inversion, and geostatistical simulation of reservoir properties. Hydraulic units are geologic layers and zones characterized by similar properties of fluid flow in porous permeable media, and are defined at well locations on the basis of logs, core measurements, and production data. However, the number of wells available for hydraulic-unit analysis is often extremely limited. In comparison, the lateral coverage and resolution of 3D-seismic data are excellent, and can thus be used to extend hydraulic-unit analysis away from well locations into the full 3D reservoir volume. We develop a probabilistic relationship between optimal 3D-seismic-data attributes and the hydraulic units that we determine at well locations. Because porosity and permeability distributions are estimated for each hydraulic flow unit as part of the process, we can use the 3D-seismic probabilistic relationships to constrain geostatistical realizations of porosity and permeability in the reservoir, to be consistent with the flow-unit analysis. Reservoir models jointly constrained by both 3D-seismic data and hydraulic flow-unit analysis have the potential to improve the processes of reservoir characterization, fluid-flow performance forecasting, and production data or 4D-seismic history matching.
This case study presents results from the Orion project within the Gulf of Mexico's Lloyd Ridge area. Difficulties arose in updating the velocity within the Cotton Valley Formation (CVF), a thin low-reflectivity layer of shale with carbonate stringers. The prestack depth migration (PSDM) common-image gathers (CIGs) and stack displayed noticeable undulations. To reduce the undulations, an offset-dependent residual moveout (RMO) picking technique was combined with high-resolution tomographic inversion to update the velocity model. This combined work flow resulted in a higher resolution velocity model, which enhanced the gather flatness and reduced the undulations of the event beneath the CVF layer.
Abstract We present a new method for seismic reservoir characterization and reservoir property modeling based on an integrated analysis of 3D seismic data and hydraulic flow units, and apply it to an example of a producing reservoir offshore Western Australia. Our method combines hydraulic unit analysis with a set of techniques for seismic reservoir characterization including: rock physics analysis, Bayesian inference, pre-stack seismic inversion and geostatistical simulation of reservoir properties. Hydraulic units are geologic layers and zones characterized by similar properties of fluid flow in porous permeable media, and are defined at well locations based on logs, core measurements and production data. However, the number of wells available for hydraulic unit analysis is often extremely limited. In comparison, the lateral coverage and resolution of 3D seismic data is excellent, and can thus be used to extend hydraulic unit analysis away from well locations into the full 3D reservoir volume. We develop a probabilistic relationship between certain 3D seismic data attributes and the hydraulic units we determine at well locations. Since porosity and permeability distributions are estimated for each hydraulic flow unit as part of the process, we can use the 3D seismic probabilistic relationships to constraint geostatistical realizations of porosity and permeability in the reservoir, to be consistent with the flow unit analysis. Reservoir models jointly constrained by both 3D seismic data and hydraulic flow unit analysis can therefore help to improve the accuracy of dynamic reservoir flow simulation and production history matching.
Abstract Hydraulic fracture monitoring from microseismic allows operators to optimize completions through a clear understanding and correlation of the reservoir response to stimulation. Furthermore it helps operators to improve production and avoid out of zone growth by identifying patterns of fluid movement, fracture growth and connectivity. These critical insights allow refinements to the treatment plan, and provide useful insights for long-term improvements regarding well spacing, well design, and completion design. Shale reservoirs with very low permeability in the nano darcy range require a large fracture network to increase well performance. In these reservoirs, unless natural pre-existing fractures and faults have been reactivated and hydraulically opened to create a complex and well-connected network, pore pressure changes do not permeate far from the fractures. As a result, the microseismic pointset roughly corresponds to the size of the real fracture network which offers a means to estimate the stimulated rock volume (SRV). Although the producing fracture network could be smaller than the total SRV by a substantial percentage, it is expected that the effective network and the total SRV show a positive correlation. However, SRV is not the only indicator of well productivity. In a given SRV, the quality of the reservoir and parameters such as fracture conductivity and fracture spacing will affect production and can have a major impact on recovery calculations. In this study, stimulated rock volumes obtained from microseismic pointsets are correlated with actual field production. The correlations are used to illustrate how this concept can optimize treatment design, well spacing, and stage spacing through correlation of the reservoir response to hydraulic fracturing and production data. The correlation between production and SRV for each well shows that larger SRVs result in higher well production regardless of the percentage of the SRV that contains proppant filled fractures. The direct relationship of the microseismic pointsets and production can be used to predict a new well's potential productivity immediately upon completion of the stimulation job. This suggests that a key completion strategy is to create a large and effective SRV to provide maximum recovery and well performance monitored microseismically to provide production prediction.
Abstract Time-lapse or 4D seismic data has proven value in reservoir management, increasing reserves and recovery by locating bypassed and undrained hydrocarbons and optimizing infill well locations and flood patterns. 4D seismic can also decrease operating costs by reducing uncertainty in the reservoir models, optimizing completions, and minimizing the number of dry holes. ExxonMobil's 4D experience demonstrates this added value to reservoir management over a wide range of geographical areas, geological settings, and production scenarios. This paper describes three 4D case studies; from the Norwegian North Sea, the Gulf of Mexico, and West Africa. In each case, the interpretation of 4D seismic data adds value to the field in ways that are not always anticipated beforehand. Most 4D seismic surveys contain at least one surprise. The value of that information can be significant. Introduction The concept behind time-lapse or 4D seismic is deceptively simple. We use repeated 3D seismic data, shot over a producing field, to help us monitor and predict the interwell changes in reservoir properties that result from the field's depletion. The fourth dimension is calendar time. Changes in reservoir properties, such as in fluid saturation and pressure, result in changes in elastic properties that, under favorable circumstances, can be detected by the seismic data. For thermal recovery processes, 4D seismic is used to detect and monitor temperature changes, and in compacting reservoirs it is used to detect porosity and stress changes. Time-lapse seismic is field-scale reservoir surveillance. However, the devil is in the details. Issues related to the application of 4D seismic technology include (1) detectability - the magnitude of the seismic response to production changes, (2) repeatability - the similarity between two seismic surveys, and (3) interpretability - how the data is integrated with geologic and engineering data. Considering these issues, each field is unique. For example, different depletion mechanisms result in different fluid-saturation distributions, different pressure variations, and, in turn, different 4D seismic responses. The 4D seismic response also depends on reservoir rock and fluid properties which are unique to each field. Repeatability of the 4D seismic image is dictated by a number of factors which include survey geometry, overburden complexity, and background noise. We have found that understanding the relationship between seismic-survey geometry repeatability and image repeatability is essential to determine the level of acquisition effort required to reduce 4D interpretation uncertainty to an acceptable level. For example, lessons learned regarding 4D acquisition in the North Sea may not translate to other basins in the world. Finally, 4D interpretation strategies depend on the objectives of the survey. Qualitative map- and volume-based approaches satisfy many reservoir management needs. However, for fields with complex depletion strategies, more quantitative interpretation methods may be required to help separate saturation from pressure changes. In addition, geologic, simulation, and geomechanical models that are conditioned using 4D interpretations are more predictive. That increased predictability extends the usefulness of the seismic data and adds value throughout the field's life cycle through better reservoir management decisions.
Wang, Joseph S.Y. (Lawrence Berkeley National Laboratory) | Smeallie, Peter H. (American Rock Mechanics Association) | Feng, Xia-Ting (Institute of Rock and Soil Mechanics, The Chinese Academy of Sciences) | Hudson, John A. (International Society of Rock Mechanics and Imperial College)