A simultaneous perturbation stochastic approximation algorithm for coupled well placement and control optimization under geologic uncertainty     

Lianlin Li  Behnam Jafarpour  M. Reza Mohammad-Khaninezhad 《Computational Geosciences》2013,17(1):167-188

Development of subsurface energy and environmental resources can be improved by tuning important decision variables such as well locations and operating rates to optimize a desired performance metric. Optimal well locations in a discretized reservoir model are typically identified by solving an integer programming problem while identification of optimal well settings (controls) is formulated as a continuous optimization problem. In general, however, the decision variables in field development optimization can include many design parameters such as the number, type, location, short-term and long-term operational settings (controls), and drilling schedule of the wells. In addition to the large number of decision variables, field optimization problems are further complicated by the existing technical and physical constraints as well as the uncertainty in describing heterogeneous properties of geologic formations. In this paper, we consider simultaneous optimization of well locations and dynamic rate allocations under geologic uncertainty using a variant of the simultaneous perturbation and stochastic approximation (SPSA). In addition, by taking advantage of the robustness of SPSA against errors in calculating the cost function, we develop an efficient field development optimization under geologic uncertainty, where an ensemble of models are used to describe important flow and transport reservoir properties (e.g., permeability and porosity). We use several numerical experiments, including a channel layer of the SPE10 model and the three-dimensional PUNQ-S3 reservoir, to illustrate the performance improvement that can be achieved by solving a combined well placement and control optimization using the SPSA algorithm under known and uncertain reservoir model assumptions.  相似文献   

An assessment of metal contamination in coastal sediments of the Caspian Sea   总被引：11，自引：0，他引：11  

de Mora S  Sheikholeslami MR  Wyse E  Azemard S  Cassi R 《Marine pollution bulletin》2004,48(1-2):61-77

An assessment of marine pollution due to metals was made in the Caspian Sea based on coastal sediment collected in Azerbaijan, Iran, Kazakhstan, Russia and Turkmenistan. Despite the high carbonate content, the distribution of most metals was largely controlled by terrigenous inputs. Several metals (As, Cr, Ni) exhibited concentrations that exceed sediment quality guidelines. Such metals have a high natural background but anthropogenic activities, notably mining, may further enhance concentrations. This would explain hot spots for Cu and Zn in Azerbaijan and Iran, and Cr at the mouth of the Ural River in Kazakhstan. Contamination by Hg was observed to the south of Baku Bay, Azerbaijan. Some anomalously high concentrations of Ba in the central Caspian are probably from offshore drilling operations, but the elevated U concentrations (up to 11.1 microg g(-1)) may be natural in origin. Several metals (Ag, Cd, Pb) have relatively low levels that pose no environmental concerns.  相似文献   

Design and implementation of a model predictive observer for AHRS     

Jafar Keighobadi  Hamid Vosoughi  Javad Faraji 《GPS Solutions》2018,22(1):29

A GPS-aided Inertial Navigation System (GAINS) is used to determine the orientation? position and velocity of ground and aerial vehicles. The data measured by Inertial Navigation System (INS) and GPS are commonly integrated through an Extended Kalman Filter (EKF). Since the EKF requires linearized models and complete knowledge of predefined stochastic noises? the estimation performance of this filter is attenuated by unmodeled nonlinearity and bias uncertainties of MEMS inertial sensors. The Attitude Heading Reference System (AHRS) is applied based on the quaternion and Euler angles methods. A moving horizon-based estimator such as Model Predictive Observer (MPO) enables us to approximate and estimate linear systems affected by unknown uncertainties. The main objective of this research is to present a new MPO method based on the duality principle between controller and observer of dynamic systems and its implementation in AHRS mode of a low-cost INS aided by a GPS. Asymptotic stability of the proposed MPO is proven by applying Lyapunov’s direct method. The field test of a GAINS is performed by a ground vehicle to assess the long-time performance of the MPO method compared with the EKF. Both the EKF and MPO estimators are applied in AHRS mode of the MEMS GAINS for the purpose of real-time performance comparison. Furthermore? we use flight test data of the GAINS for evaluation of the estimation filters. The proposed MPO based on both the Euler angles and quaternion methods yields better estimation performances compared to the classic EKF.  相似文献   

Perceived and actual risks of drought: household and expert views from the lower Teesta River Basin of northern Bangladesh     

Salam  Roquia  Ghose  Bonosri  Shill  Badhon Kumar  Islam  Md. Aminul  Islam  Abu Reza Md. Towfiqul  Sattar  Md. Abdus  Alam  G. M. Monirul  Ahmed  Bayes 《Natural Hazards》2021,108(3):2569-2587

Natural Hazards - Disaster risk perception and risk appraisal are essential in formulating an appropriate disaster risk reduction policy. This study examines the actual vs perceived drought risks...  相似文献   

Nexus between vulnerability and adaptive capacity of drought-prone rural households in northern Bangladesh     

Salam  Roquia  Towfiqul Islam  Abu Reza Md.  Shill  Badhon Kumar  Monirul Alam  G. M.  Hasanuzzaman  Md.  Morshadul Hasan  Md.  Ibrahim  Sobhy M.  Shouse  Roger C. 《Natural Hazards》2021,106(1):509-527

Natural Hazards - Bangladesh is one of the world’s most climate-vulnerable countries. The appraisal of household vulnerability and capacity to adapt under climate change is therefore crucial...  相似文献   

Landslide susceptibility mapping using machine learning algorithms and comparison of their performance at Abha Basin,Asir Region,Saudi Arabia     

Ahmed Mohamed Youssef  Hamid Reza Pourghasemi 《地学前缘(英文版)》2021,12(2):639-655

The current study aimed at evaluating the capabilities of seven advanced machine learning techniques(MLTs),including,Support Vector Machine(SVM),Random Forest(RF),Multivariate Adaptive Regression Spline(MARS),Artificial Neural Network(ANN),Quadratic Discriminant Analysis(QDA),Linear Discriminant Analysis(LDA),and Naive Bayes(NB),for landslide susceptibility modeling and comparison of their performances.Coupling machine learning algorithms with spatial data types for landslide susceptibility mapping is a vitally important issue.This study was carried out using GIS and R open source software at Abha Basin,Asir Region,Saudi Arabia.First,a total of 243 landslide locations were identified at Abha Basin to prepare the landslide inventory map using different data sources.All the landslide areas were randomly separated into two groups with a ratio of 70%for training and 30%for validating purposes.Twelve landslide-variables were generated for landslide susceptibility modeling,which include altitude,lithology,distance to faults,normalized difference vegetation index(NDVI),landuse/landcover(LULC),distance to roads,slope angle,distance to streams,profile curvature,plan curvature,slope length(LS),and slope-aspect.The area under curve(AUC-ROC)approach has been applied to evaluate,validate,and compare the MLTs performance.The results indicated that AUC values for seven MLTs range from 89.0%for QDA to 95.1%for RF.Our findings showed that the RF(AUC=95.1%)and LDA(AUC=941.7%)have produced the best performances in comparison to other MLTs.The outcome of this study and the landslide susceptibility maps would be useful for environmental protection.  相似文献   

Using high-resolution satellite imagery to provide a relief priority map after earthquake     

Hamid Reza Ranjbar  Alireza A. Ardalan  Hamid Dehghani  Mohammad Reza Saradjian 《Natural Hazards》2018,90(3):1087-1113

After the earthquake occurrence, collecting correct information about the extent of damage is essential for managing critical conditions and allocating limited resources. The prepared building damage maps sometimes bring about waste of time required for rescuing individuals under the rubble by wrongly conducting rescue teams toward regions with a lower rescue priority. In this research, an algorithm based on using a proposed standard at database level was developed to prioritize damaged buildings by considering five key elements of land use type, the degree of damage to buildings, the land use differentiation index, time of the highest population density in each land use, and time of disaster’s incidence. The steps of the proposed method which was implemented in the MATLAB environment include: detecting buildings on the pre- and post-event imagery, implementing texture features for each candidate building, choosing the optimal features by genetic algorithm, determining the degree of building damage in three classes of negligible damage, substantial damage, and heavy damage by using the difference between chosen features as inputs of the designed neurofuzzy inference system. Data collected from field observations were compared to the output obtained from the proposed algorithm. This comparison presented a general accuracy of 88% and Kappa coefficient of 79% in the classification of buildings into three damage classes. The proposed standard then was used for classifying damaged buildings into relief priorities of high, medium, and low. Findings revealed that the relief priority map could be a basis for correct guidance of relief and rescue teams during crucial times following earthquakes.  相似文献   

Pressuremeter Modulus and Limit Pressure of Clayey Soils Using <Emphasis Type="Italic">GMDH</Emphasis>-Type Neural Network and Genetic Algorithms     

Reza Ziaie Moayed  Afshin Kordnaeij  Hossein Mola-Abasi 《Geotechnical and Geological Engineering》2018,36(1):165-178

Pressuremeter modulus (\(E_{M}\)) and limit pressure (\(P_{L}\)) are used for the calculation of the settlement and bearing capacity of foundation respectively. As the determination of these parameters from pressuremeter test (PMT) is relatively time-consuming and expensive, various empirical correlations have been proposed to correlate the \(E_{M}\) and \(P_{L}\) to other soil parameters. For the existing equations are incapable of estimating these PMT parameters well, in present research group method of data handling type neural network is used to estimate the \(E_{M}\) and \(P_{L}\) of clayey soils. The \(E_{M}\) and \(P_{L}\) were modeled as a function of three variables including the moisture content (\(\omega\)), plasticity index and corrected SPT blow counts (\(N_{60}\)). A database containing 51 data sets have been used for training and testing of the models. The performances of proposed models are compared with those of existing empirical equations. The results demonstrate that appreciable improvement with respect to the other correlations has been achieved. At the end, sensitivity analysis of the obtained models has been performed to study the influence of input parameters on model outputs and shows that the \(N_{60}\) is the most influential parameter on the PMT parameters.  相似文献   

A hybrid clustering-fusion methodology for land subsidence estimation     

Taravatrooy  Narges  Nikoo  Mohammad Reza  Sadegh  Mojtaba  Parvinnia  Mohammad 《Natural Hazards》2018,93(2):905-920

In many parts of Canada, limited data are available for hydrodynamic model inputs, and the ability to generate quality flood grids through 1D, 2D or 3D methods is nonviable. In this paper, the capability of simplified flood models, which rely solely on digital terrain models (DTMs), was explored to assess the quality and speed of their results. Results were validated against historic floods in two locations. Three non-physics-based simplified conceptual flood models were tested: (1) planar method, (2) inclined plane and (3) height above nearest drainage network (HAND) model. The accuracy and performance were evaluated using three criteria: inundation extent, water depth and computation time. Findings show that the HAND model is the best predictor of inundation extent, with Probability of Detection and Critical Success Index being higher than 0.90 in both study areas. Though the preprocessing time for the HAND model is lengthy, once completed, the time to simulate flooding at a variety of water levels is rapid, making this model the most suitable choice for web-based, on-demand flood inundation mapping. Knowledge of the fit of these flood models and associated uncertainty can be helpful to emergency managers such that they can better understand exposure and vulnerability while preparing flood response plans.  相似文献   

Assessing Lateral Continuity within the Yammama Reservoir in the Foroozan Oilfield, Offshore Iran: An Integrated Study     

Payam HASSANZADEH  Ahmad Reza RABBANI  Ardeshir HEZARKHANI  Saeed KHAJOOIE 《《地质学报》英文版》2018,92(6):2405-2415

Located in Iranian sector of the Persian Gulf, Foroozan Oilfield has been producing hydrocarbons via seven different reservoirs since the 1970s. However, understanding fluid interactions and horizontal continuity within each reservoir has proved complicated in this field. This study aims to determine the degree of intra-reservoir compartmentalization using gas geochemistry, light hydrocarbon components, and petroleum bulk properties, comparing the results with those obtained from reservoir engineering indicators. For this purpose, a total of 11 samples of oil and associated gas taken from different producing wells in from the Yammama Reservoir were selected. Clear distinctions, in terms of gas isotopic signature and composition, between the wells located in northern and southern parts of the reservoir (i.e. lighter δ13C1, lower methane concentration, and negative sulfur isotope in the southern part) and light hydrocarbon ratios (e.g. nC7/toluene, 2,6-dmC7/1,1,3-tmcyC5 and m-xylene/4-mC8) in different oil samples indicated two separate compartments. Gradual variations in a number of petroleum bulk properties (API gravity, V/Ni ratios and asphaltene concentration) provided additional evidence on the reservoir-filling direction, signifying that a horizontal equilibrium between reservoir fluids across the Yammama Reservoir is yet to be achieved. Finally, differences in water-oil contacts and reservoir types further confirmed the compartmentalization of the reservoir into two separate compartments.  相似文献