بررسی فرونشست زمین در اثر استخراج مواد نفتی با استفاده از روش تداخل سنجی رادار

تولید از مخازن هیدروکربوری، سبب افت فشار منفذی در این مخازن می‌شود. این افت فشار، تنش ناشی از رسوبات روباره‌ی سنگ مخزن را که پیش از عملیات برداشت، توسط فشار سیال داخل مخزن و سنگ‌های پوششی کنترل می‌شد افزایش داده و موجب تراکم محیط متخلخل اطراف می‌شود. در صورتی که میزان تراکم مخزن از حدی فراتر رود، سنگ‌های روباره در اثر وزن خود شروع به فرونشست خواهند کرد که این امر می‌تواند تأثیرات مخربی از جمله شکستگی چاه‌ها، مچاله شدگی لوله‌های جداری و خسارات سرچاهی را به دنبال داشته و در نتیجه فرآیند تولید از این مخازن را با مشکل جدی مواجه کند. بنابراین مطالعه پدیده‌ی فرونشست ناشی از بهره‌برداری منابع هیدروکربوری، حائز اهمیت بوده و نیاز به توجه و بررسی دقیق دارد. برای این منظور روش‌های متعددی می‌تواند مورد‌ استفاده قرار گیرد؛ لذا روشی که دارای سرعت و دقت بالا و هزینه‌ی پایین باشد همواره در اولویت خواهد بود. بدلیل هزینه‌بر بودن روش‌های ترازیابی دقیق و نقشه‌برداری زمینی و نیز عدم دسترسی به مشاهدات آنها در برخی شرایط خاص، بکارگیری روشی سریع‌تر و ارزان‌تر پیشنهاد می‌شود. خوشبختانه پیشرفت در زمینه‌ی ماهواره و تکنولوژی رادار باعث شده است که قادر به اندازه‌گیری جابجایی‌هایی بسیار کوچک سطح زمین در نواحی مستعد جابجایی از جمله میدان‌های تحت برداشت سیال‌های زیر‌سطحی باشیم. روش تداخل‌سنجی تفاضلی رادار (InSAR) فناوری نوینی است که از تصاویر ماهواره‌ای جهت آشکارسازی دگرریختی شکل سطح زمین استفاده می‌کند. در این راستا دو میدان بزرگ نفتی یکی واقع در منطقه‌ی جنوب غربی ایران و دیگری در کالیفرنیای مرکزی توسط تکنیک تداخل‌سنجی راداری مورد بررسی قرار گرفت. نتایج بدست آمده بیانگر کارایی مناسب این روش به منظور بررسی جابجایی ناشی از فرونشست در میادین مذکور می‌باشد

Radar interferometry for monitoring land subsidence and coastal change in the Nile Delta, Egypt

Land subsidence and coastal erosion are worldwide problems, particularly in densely populated deltas. The Nile Delta is no exception. Currently, it is undergoing land subsidence and is simultaneously experiencing retreat of its coastline. The impacts of these long-term interrelated geomorphic problems are heightened by the economic, social and historical importance of the delta to Egypt. Unfortunately, the current measures of the rates of subsidence and coastal erosion in the delta are rough estimates at best. Sustainable development of the delta requires accurate and detailed spatial and temporal measures of subsidence and coastal retreat rates. Radar interferometry is a unique remote sensing approach that can be used to map topography with 1 m vertical accuracy and measure surface deformation with 1 mm level accuracy. Radar interferometry has been employed in this dissertation to measure urban subsidence and coastal change in the Nile Delta. Synthetic Aperture Radar (SAR) data of 5.66 cm wavelength acquired by the European Radar Satellites (ERS-1 and ERS- 2) spanning eight years (1993-2000) have been used in this investigation. The ERS data have been selected because the spatial and temporal coverage, as well as the short wavelength, are appropriate to measure the slow rate of subsidence in the delta. The ERS tandem coherence images are also appropriate for coastal change detection. The magnitude and pattern of subsidence are detected and measured using Permanent Scatterer interferometry. The measured rates of subsidence in greater Cairo, Mansura, and Mahala are 7, 9, and 5 mm yr-1, respectively. Areas of erosion and accretion in the eastern side of the delta are detected using the ERS tandem coherence and the ERS amplitude images. The average measured rates of erosion and accretion are -9.57 and +5.44 m yr-1, respectively. These measured rates pose an urgent need of regular monitoring of subsidence and coastline retreat in the delta. This study highlighted the feasibility of applying Permanent Scatterer interferometry in inappropriate environment for conventional SAR interferometry. The study addressed possibilities and limitations for successful use of SAR interferometry within the densely vegetated delta and introduced alternative strategies for further improvement of SAR interferometric measurements in the delta

Integration of Synthetic Aperture Radar Interferometry (InSAR) and Geographical Information Systems (GIS) for monitoring mining induced surface deformations

Surface subsidence induced by mining is a source of risk to people, equipment and environment. It may also disrupt mining schedules and increase the cost of mine safety. To provide accurate assessment of the surface subsidence and its level of impact on mine production and environment, it is necessary to develop and introduce comprehensive subsidence monitoring systems. Current techniques for monitoring of surface deformation are usually based on classical survey principles. In general these techniques have disadvantages that limit their applicability: they follow point-by-point data collection techniques, they are relatively time-consuming and costly, they usually cover only a small area, they are not applicable for the monitoring of inaccessible areas and they are not able to collect data continuously.As a complementary or alternative technique, the thesis discusses the applicability of SAR interferometry for monitoring mining induced deformations. InSAR is a remote sensing technique that makes use of Synthetic Aperture Radar (SAR) observations to acquire change in terrain topography. In spite of the widespread application of the technique for monitoring large-scale deformations of the Earth crust, specific modifications are necessary for utilising the technology within a mining context. Limitations, such as difficulty to resolve deformation for a high gradient slope, difficulty to retrieve subsidence for localised highly dynamic ground movements and the unavailability of SAR images with the desired specifications restrict the potential to monitor high rate, localised mine subsidence on day-to-day basis.The secondary aim of the thesis is to present integration of InSAR and GIS in order to propose an optimum methodology for processing of InSAR data to determine mine subsidence. The presented research also involves detailed analysis of InSAR limitations. This in consequence has led to suggestions on how to improve current InSAR capability with respect to the mining needs.The thesis introduces a set of new GIS-based tools and methodologies that are integrated into a conventional InSAR processing technique, to further improve and facilitate application of InSAR in mining. The developed tools and techniques cover the three main stages of data processing (pre-processing, processing and postprocessing). The researcher tried to address InSAR.’s limitations associated with mining related applications and also to provide practical solutions to resolve these issues

Cell-Based Deformation Monitoring via 3D Point Clouds

Deformation is one of the most important phenomena in environmental science and engineering. Deformation of artificial and natural objects happens worldwide, such as structural deformation, landslide, subsidence, erosion, and rockfall. Monitoring and assessment of such deformation process is not only scientifically interesting, but also beneficial to hazard/risk control and prediction. In addition, it is also useful for regional planning and development. Deformation monitoring was driven by geodetic observations in the field of traditional geodetic surveying, based on the measurement of sparse points in a control network. Recently, with the rapid development of terrestrial LiDAR techniques, millions of points with associated three-dimensional coordinates (known as "3D point clouds") can be promptly captured in a few minutes. Compared to traditional surveying, terrestrial LiDAR offers great potential for deformation monitoring, because of various advantages such as fast data capture, high data density, and precise 3D object representation. By analysing 3D point clouds, the objective of this thesis is to provide an effective and efficient approach for deformation monitoring. Towards this goal, this thesis designs a new concept of "deformation map" for deformation representation and a novel "cell-based approach" for deformation computation. The main outcome of this thesis is a novel and rich approach that is able to automatically and incrementally compute a deformation map that enables a better understanding of structural and natural hazards with heterogeneous deformation characteristics. This work includes several dedicated contributions as follows. Hybrid Deformation Modelling. This thesis firstly provides a comprehensive investigation on the modelling requirements of various deformation phenomena. The requirements concern three main aspects, i.e., what has deformation (deformation object), which type of deformation, and how to describe deformation. Based on this detailed requirement analysis, we propose a rich and hybrid deformation model. This model is composed of meta-deformation, sub-deformation and deformation map, corresponding to deformation for a small cell, for a partial area, and for the whole object, respectively. Cell-based Deformation Computation. In order to automatically and incrementally extract heterogeneous deformation of the whole monitored object, we bring the "cell" concept into deformation monitoring. This thesis builds a cell-based deformation computing framework, which consists of three key steps: split, detect, and merge. Split is to divide the space of the object into many cells (uniform or irregular); detect is to extract the meta-deformation for individual cells by analysing the inside point clouds at two epochs; and merge is to group adjacent cells with similar deformation together and to form a consistent sub-deformation. As the final result, an informative deformation map is computed for describing the deformation for the whole object. Evaluation of Cell-based Approach. To evaluate such hybrid modelling and cell-based deformation computation, this thesis extensively studies both synthetic and real-life point cloud datasets: (1) by imitating a landslide scenario, we generate synthetic data using Matlab programming and practical settings, and compare the cell-based approach with traditional non-cell based geodetic methods; (2) by analysing two real-life cases of deformation in Switzerland, we further validate our approach and compare the results with third party sources (e.g., results provided by a surveying company, results computed by using a commercial software like 3DReshaper). Extension of Cell-based Approach. At the last stages of this thesis work, we particularly focus on providing several technical extensions to enhance this cell-based deformation monitoring approach. The main extensions include: (1) supporting dynamic cells instead of uniform cells when splitting the entire object space, (2) finding cell correspondence for the deformation scenarios that have large deformation like rockfalls, (3) movement tracking with data-driven cells which have irregular cell shape that can be automatically determined by the deformation boundary itself, (4) designing an adaptive modelling strategy that is able to accordingly select a suitable model for detecting meta-deformation of cells, and (5) computing deformation evolution for a monitored object with more than two epochs of point cloud datasets

Monitoring Oil Reservoir Deformations by Measuring Ground Surface Movements

It has long been known that any activity that results in changes in subsurface pressure, such as hydrocarbon production or waste or water reinjection, also causes underground deformations and movement, which can be described in terms of volumetric changes. Such deformations induce surface movement, which has a significant environmental impact. Induced surface deformations are measurable as vertical displacements; horizontal displacements; and tilts, which are the gradient of the surface deformation. The initial component of this study is a numerical model developed in C++ to predict and calculate surface deformations based on assumed subsurface volumetric changes occurring in a reservoir. The model is based on the unidirectional expansion technique using equations from Okada’s theory of dislocations (Okada, 1985). A second numerical model calculates subsurface volumetric changes based on surface deformation measurements, commonly referred to as solving for the inverse case. The inverse case is an ill-posed problem because the input is comprised of measured values that contain error. A regularization technique was therefore developed to help solve the ill-posed problem. A variety of surface deformation data sets were analyzed in order to determine the surface deformation input data that would produce the best solution and the optimum reconstruction of the initial subsurface volumetric changes. Tilt measurements, although very small, were found to be much better input than vertical displacement data for finding the inverse solution. Even in an ideal case with 0 % error, tilts result in a smaller RMSE (about 12 % smaller in the case studied) and thus a better resolution. In realistic cases with error, adding only 0.55 % of the maximum random error in the surface displacement data affects the back-calculated results to a significant extent: the RMSE increased by more than 13 times in the case studied. However, in an identical case using tilt measurements as input, adding 20 % of the maximum surface tilt value as random error increased the RMSE by 7 times, and remodelling the initial distribution of the volumetric changes in the subsurface was still possible. The required area of observation can also be reduced if tilt measurements are used. The optimal input includes tilt measurements in both directions: dz/dx and dz/dy. iv With respect to the number of observation points chosen, when tilts are used with an error of 0 %, very good resolution is obtainable using only 0.4 % of the unknowns as the number of benchmarks. For example, using only 10 observation points for a reservoir with 2500 elements, or unknowns resulted in an acceptable reconstruction. With respect to the sensitivity of the inverse solution to the depth of the reservoir and to the geometry of the observation grid, the deeper the reservoir, the more ill-posed the problem. The geometry of the benchmarks also has a significant effect on the solution of the inverse problem

CO2 CAPTURE PROJECT - AN INTEGRATED, COLLABORATIVE TECHNOLOGY DEVELOPMENT PROJECT FOR NEXT GENERATION CO2 SEPARATION, CAPTURE AND GEOLOGIC SEQUESTRATION

The CO{sub 2} Capture Project (CCP) is a joint industry project, funded by eight energy companies (BP, ChevronTexaco, EnCana, Eni, Norsk Hydro, Shell, Statoil, and Suncor) and three government agencies (1) European Union (DG Res & DG Tren), (2) Norway (Klimatek) and (3) the U.S.A. (Department of Energy). The project objective is to develop new technologies, which could reduce the cost of CO{sub 2} capture and geologic storage by 50% for retrofit to existing plants and 75% for new-build plants. Technologies are to be developed to ''proof of concept'' stage by the end of 2003. The project budget is approximately $24 million over 3 years and the work program is divided into eight major activity areas: (1) Baseline Design and Cost Estimation--defined the uncontrolled emissions from each facility and estimate the cost of abatement in$/tonne CO{sub 2}. (2) Capture Technology, Post Combustion: technologies, which can remove CO{sub 2} from exhaust gases after combustion. (3) Capture Technology, Oxyfuel: where oxygen is separated from the air and then burned with hydrocarbons to produce an exhaust with high CO{sub 2} for storage. (4) Capture Technology, Pre -Combustion: in which, natural gas and petroleum coke are converted to hydrogen and CO{sub 2} in a reformer/gasifier. (5) Common Economic Model/Technology Screening: analysis and evaluation of each technology applied to the scenarios to provide meaningful and consistent comparison. (6) New Technology Cost Estimation: on a consistent basis with the baseline above, to demonstrate cost reductions. (7) Geologic Storage, Monitoring and Verification (SMV): providing assurance that CO{sub 2} can be safely stored in geologic formations over the long term. (8) Non-Technical: project management, communication of results and a review of current policies and incentives governing CO{sub 2} capture and storage. Technology development work dominated the past six months of the project. Numerous studies are making substantial progress towards their goals. Some technologies are emerging as preferred over others. Pre-combustion Decarbonization (hydrogen fuel) technologies are showing good progress and may be able to meet the CCP's aggressive cost reduction targets for new-build plants. Chemical looping to produce oxygen for oxyfuel combustion shows real promise. As expected, post-combustion technologies are emerging as higher cost options that may have niche roles. Storage, measurement, and verification studies are moving rapidly forward. Hyper-spectral geo-botanical measurements may be an inexpensive and non-intrusive method for long-term monitoring. Modeling studies suggest that primary leakage routes from CO{sub 2} storage sites may be along wellbores in areas disturbed by earlier oil and gas operations. This is good news because old wells are usually mapped and can be repaired during the site preparation process. Many studies are nearing completion or have been completed. Their preliminary results are summarized in the attached report and presented in detail in the attached appendices