气候影响评价中统计降尺度若干问题的探讨

全球气候模式是目前研究未来气候变化的重要工具,然而其较低的空间分辨率使其难以被直接用于区域尺度的气候影响评价中,统计降尺度常常被用于弥补这一不足。对统计降尺度的3种主要方法:转化函数法,天气分型法和天气发生器法的最新研究进展进行了归纳;论述了统计降尺度中的各种不确定性;总结了统计降尺度在中国的发展和应用。统计降尺度与动力降尺度的比较和结合、极端事件的降尺度以及统计降尺度的不确定性将成为未来的主要发展方向。     

A stochastic inversion workflow for monitoring the distribution of CO<Subscript>2</Subscript> injected into deep saline aquifers

We present a two-step stochastic inversion approach for monitoring the distribution of CO₂ injected into deep saline aquifers for the typical scenario of one single injection well and a database comprising a common suite of well logs as well as time-lapse vertical seismic profiling (VSP) data. In the first step, we compute several sets of stochastic models of the elastic properties using conventional sequential Gaussian co-simulations (SGCS) representing the considered reservoir before CO₂ injection. All realizations within a set of models are then iteratively combined using a modified gradual deformation algorithm aiming at reducing the mismatch between the observed and simulated VSP data. In the second step, these optimal static models then serve as input for a history matching approach using the same modified gradual deformation algorithm for minimizing the mismatch between the observed and simulated VSP data following the injection of CO₂. At each gradual deformation step, the injection and migration of CO₂ is simulated and the corresponding seismic traces are computed and compared with the observed ones. The proposed stochastic inversion approach has been tested for a realistic, and arguably particularly challenging, synthetic case study mimicking the geological environment of a potential CO₂ injection site in the Cambrian-Ordivician sedimentary sequence of the St. Lawrence platform in Southern Québec. The results demonstrate that the proposed two-step reservoir characterization approach is capable of adequately resolving and monitoring the distribution of the injected CO₂. This finds its expression in optimized models of P- and S-wave velocities, density, and porosity, which, compared to conventional stochastic reservoir models, exhibit a significantly improved structural similarity with regard to the corresponding reference models. The proposed approach is therefore expected to allow for an optimal injection forecast by using a quantitative assimilation of all available data from the appraisal stage of a CO₂ injection site.     

Characterizing the vadose zone and a perched aquifer near the Vosges ridge at the La Soutte experimental site,Obernai, France

We consider a series of hydrogeophysical techniques that provide a multiscale investigation of the water content in the vadose zone and of the perched aquifer at the experimental site of “La Soutte” in the Vosges Mountains (France). It is located in a catchment area where several springs and streams occur along fractured volcanic and weathered plutonic rocks. The site is the object of a long-term study that uses both continuous and repeated measurements to monitor hydrogeological processes. The main results from AMT and DC resistivity techniques allow the determination of a high-resolution 3D resistivity model over a large range of depths (from 10⁰ to 10³ m). We discuss their use and propose a hydrogeological model (porosity, water conductivity and water content). We also use MRS and GPR for a detailed investigation of the shallow part of the catchment that consists of soil and weathered rocks of highly varying thickness (0 to 15 m). MRS is used to map the thickness and total water volume content by unit surface of the saturated weathered zone. It also yields estimates of the vadose zone thickness through the depth to the top of the saturated zone. Moreover, we show results from GPR CMP measurements that yield estimates of the water content and porosity in the shallowest layer (0–30 cm) by simple interpretation of the ground direct wave.     

水文物探测井解释模型研究

本文从目前国内水文物探测井技术的现状和常规技术方法出发，通过对大量第三系、第四系松散岩石孔隙含水层水文物探测井实际资料的研究，对含水层的矿化度ＣＷ、导水系数Ｔ、渗透系数Ｋ、单位涌水量ｑ、孔隙度ψ、粒度中值Ｍｄ和泥质含量Ｖｓｈ等７个测井解释模型进行了探讨研究，并给出了具体方法。     

Joint hydrogeophysical inversion: state estimation for seawater intrusion models in 3D

Seawater intrusion (SWI) is a complex process, where 3D modeling is often necessary in order to monitor and manage the affected aquifers. Here, we present a synthetic study to test a joint hydrogeophysical inversion approach aimed at solving the inverse problem of estimating initial and current saltwater distribution. First, we use a 3D groundwater model for variable density flow based on discretized flow and solute mass balance equations. In addition to the groundwater model, a 3D geophysical model was developed for direct current resistivity imaging and inversion. The objective function of the coupled problem consists of data misfit and regularization terms as well as a coupling term that relates groundwater and geophysical states. We present a novel approach to solve the inverse problem using an alternating direction method of multipliers (ADMM) to minimize this coupled objective function. ADMM enables to treat the groundwater and geophysical part separately and thus use the existing software with minor changes. To further reduce the computational cost, the sensitivities are derived analytically for the discretized system of equations, which allows us to efficiently compute the gradients in the minimization procedure. The method was tested on different synthetic scenarios with groundwater and geophysical data represented by solute mass fraction data and direct current resistivity data. With the ADMM approach, we were able to obtain better estimates for the solute distribution compared to just considering each data separately, solving the problem with a simple coupled approach or by a direct substitution of the coupling constraint.     

An integrative approach to robust design and probabilistic risk assessment for CO<Subscript>2</Subscript> storage in geological formations

CO₂ storage in geological formations is currently being discussed intensively as a technology with a high potential for mitigating CO₂ emissions. However, any large-scale application requires a thorough analysis of the potential risks. Current numerical simulation models are too expensive for probabilistic risk analysis or stochastic approaches based on a brute-force approach of repeated simulation. Even single deterministic simulations may require parallel high-performance computing. The multiphase flow processes involved are too non-linear for quasi-linear error propagation and other simplified stochastic tools. As an alternative approach, we propose a massive stochastic model reduction based on the probabilistic collocation method. The model response is projected onto a higher-order orthogonal basis of polynomials to approximate dependence on uncertain parameters (porosity, permeability, etc.) and design parameters (injection rate, depth, etc.). This allows for a non-linear propagation of model uncertainty affecting the predicted risk, ensures fast computation, and provides a powerful tool for combining design variables and uncertain variables into one approach based on an integrative response surface. Thus, the design task of finding optimal injection regimes explicitly includes uncertainty, which leads to robust designs with a minimum failure probability. We validate our proposed stochastic approach by Monte Carlo simulation using a common 3D benchmark problem (Class et al., Comput Geosci 13:451–467, 2009). A reasonable compromise between computational efforts and precision was reached already with second-order polynomials. In our case study, the proposed approach yields a significant computational speed-up by a factor of 100 compared with the Monte Carlo evaluation. We demonstrate that, due to the non-linearity of the flow and transport processes during CO₂ injection, including uncertainty in the analysis leads to a systematic and significant shift of the predicted leakage rates toward higher values compared with deterministic simulations, affecting both risk estimates and the design of injection scenarios.     

地质统计学反演技术研究与应用

实现油气储层的精细描述和建模,是石油勘探和开发过程中十分重要的环节,常规的确定性反演由于受到地震频带限制,反演结果垂向分辨率低,往往难以识别单砂体厚度较小的储层分布。通过在A油田应用的实践表明,应用高密度采集的地震数据,开展基于随机建模技术的地质统计学反演方法,能够有效地综合地质、测井和三维地震数据,明显提高反演结果的垂向分辨率,可以更好地识别薄层砂体,为精细储层识别、油藏建模提供可靠依据。     

Stochastic analysis of unsaturated seepage through randomly heterogeneous earth embankments

Spatial variability of material properties is inherent in both natural soil deposits and earth structures, yet it is often ignored during geotechnical design. With the objective of developing novel methods for assessing the effects of soil variability on groundwater flow, this study presents a stochastic finite element model of seepage through a flood defense embankment with randomly heterogeneous material properties. Stochastic modeling is undertaken by means of a Monte Carlo simulation which involves a large number of finite element analyses, each with randomly varied porosity at element level, which leads to a corresponding random variation of both permeability and water retention properties across the embankment domain. This provides a statistical distribution of responses, such as total flow rate and time to reach steady state, instead of a single deterministic result as in conventional studies of seepage through unsaturated heterogeneous soils. As the degree of heterogeneity increases, water tends to flow along the most permeable paths inside the soil mass, resulting in an irregular shape of the predicted wetting fronts and pore pressure contours. The mean and standard deviation of the computed quantities strongly depend on the statistics of the input porosity field. Simulations are also conducted to compare the statistical variation of flow rate with and without dependency of the water retention curve on porosity. With recent growth in computer speed, stochastic finite element models based on the Monte Carlo approach can become a powerful design tool, especially if a quantitative assessment of geotechnical risks is required. Copyright © 2011 John Wiley & Sons, Ltd.     

http://www.sciencedirect.com/science/article/pii/S1674987115001322

Zircon U-Pb geochronology has become a keystone tool across Earth science,arguably providing the gold standard in resolving deep geological time.The development of rapid in situ analysis of zircon（via laser ablation and secondary ionization mass spectrometry） has allowed for large amounts of data to be generated in a relatively short amount of time and such large volume datasets offer the ability to address a range of geological questions that would otherwise remain intractable（e.g.detrital zircons as a sediment fingerprinting method）.The ease of acquisition,while bringing benefit to the Earth science community,has also led to diverse interpretations of geochronological data.In this work we seek to refocus U-Pb zircon geochronology toward best practice by providing a robust statistically coherent workflow.We discuss a range of data filtering approaches and their inherent limitations（e.g.discordance and the reduced chi-squared;MSWD）.We evaluate appropriate mechanisms to calculate the most geologically appropriate age from both ²³⁸U/²⁰⁶Pb and ²⁰⁷Pb/²⁰⁶Pb ratios and demonstrate the cross over position when chronometric power swaps between these ratios.As our in situ analytical techniques become progressively more precise,appropriate statistical handing of U-Pb datasets will become increasingly pertinent.     

Mechanical and hydraulic properties of rocks related to induced seismicity

Witherspoon, P.A. and Gale, J.E., 1977. Mechanical and hydraulic properties of rocks related to induced seismicity. Eng. Geol., 11(1): 23–55.The mechanical and hydraulic properties of fractured rocks are considered with regard to the role they play in induced seismicity. In many cases, the mechanical properties of fractures determine the stability of a rock mass. The problems of sampling and testing these rock discontinuities and interpreting their non-linear behavior are reviewed. Stick slip has been proposed as the failure mechanism in earthquake events. Because of the complex interactions that are inherent in the mechanical behavior of fractured rocks, there seems to be no simple way to combine the deformation characteristics of several sets of fractures when there are significant perturbations of existing conditions. Thus, the more important fractures must be treated as individual components in the rock mass.In considering the hydraulic properties, it has been customary to treat a fracture as a parallel-plate conduit and a number of mathematical models of fracture systems have adopted this approach. Non-steady flow in fractured systems has usually been based on a two-porosity model, which assumes the primary (intergranular) porosity contributes only to storage and the secondary (fracture) porosity contributes only to the overall conductivity. Using such a model, it has been found that the time required to achieve quasi-steady state flow in a fractured reservoir is one or two orders of magnitude greater than it is in a homogeneous system. In essentially all of this work, the assumption has generally been made that the fractures are rigid.However, it is clear from a review of the mechanical and hydraulic properties that not only are fractures easily deformed but they constitute the main flow paths in many rock masses. This means that one must consider the interaction of mechanical and hydraulic effects. A considerable amount of laboratory and field data is now available that clearly demonstrates this stress-flow behavior. Two approaches have been used in attempting to numerically model such behavior: (1) continuum models, and (2) discrete models. The continuum approach only needs information as to average values of fracture spacing and material properties. But because of the inherent complexity of fractured rock masses and the corresponding decrease in symmetry, it is difficult to develop an equivalent continuum that will simulate the behavior of the entire system. The discrete approach, on the other hand, requires details of the fracture geometry and material properties of both fractures and rock matrix. The difficulty in obtaining such information has been considered a serious limitation of discrete models, but improved borehole techniques can enable one to obtain the necessary data, at least in shallow systems. The possibility of extending these methods to deeper fracture systems needs more investigation. Such data must be considered when deciding whether to use a continuum or discrete model to represent the interaction of rock and fluid forces in a fractured rock system, especially with regard to the problem of induced seismicity. When one is attempting to alter the pressure distribution in a fault zone by injection or withdrawal of fluids, the extent to which this can be achieved will be controlled in large measure by the behavior of the fractures that communicate with the borehole. Since this is essentially a point phenomenon, i.e., the changes will propagate from a relatively small region around the borehole, the use of a discrete model would appear to be preferable.     

A stochastic approach to sieving kinetics

A model of the batch sieving process based on a stochastic approach is presented. The model indicates that there is an inherent uncertainty associated with sieving results which is a function of the mean sieving rate, degree of choking and sieving time. The model suggests that choking of sieve apertures may lead to a disproportionately high degree of uncertainty. Experimental data for a sonic sifter device gave good semi-quantitative agreement with the model, while that for a Rotap device gave qualitative agreement.     

Seismogenic Structure around the Epicenter of the May 12,2008 Wenchuan Earthquake from Micro-seismic Tomography

A three-dimensional local-scale P-velocity model down to 25 km depth around the main shock epicenter region was constructed using 83821 event-to-receiver seismic rays from 5856 aftershocks recorded by a newly deployed temporary seismic network.Checkerboard tests show that our tomographic model has lateral and vertical resolution of～2 km.The high-resolution P-velocity model revealed interesting structures in the seismogenic layer:(1) The Guanxian-Anxian fault, Yingxiu-Beichuan fault and Wenchuan-Maoxian f...     

Impact of model complexity and multi-scale data integration on the estimation of hydrogeological parameters in a dual-porosity aquifer

This study investigates the impact of model complexity and multi-scale prior hydrogeological data on the interpretation of pumping test data in a dual-porosity aquifer (the Chalk aquifer in England, UK). In order to characterize the hydrogeological properties, different approaches ranging from a traditional analytical solution (Theis approach) to more sophisticated numerical models with automatically calibrated input parameters are applied. Comparisons of results from the different approaches show that neither traditional analytical solutions nor a numerical model assuming a homogenous and isotropic aquifer can adequately explain the observed drawdowns. A better reproduction of the observed drawdowns in all seven monitoring locations is instead achieved when medium and local-scale prior information about the vertical hydraulic conductivity (K) distribution is used to constrain the model calibration process. In particular, the integration of medium-scale vertical K variations based on flowmeter measurements lead to an improvement in the goodness-of-fit of the simulated drawdowns of about 30%. Further improvements (up to 70%) were observed when a simple upscaling approach was used to integrate small-scale K data to constrain the automatic calibration process of the numerical model. Although the analysis focuses on a specific case study, these results provide insights about the representativeness of the estimates of hydrogeological properties based on different interpretations of pumping test data, and promote the integration of multi-scale data for the characterization of heterogeneous aquifers in complex hydrogeological settings.     

Conditioning Fractal (fBm/fGn) Porosity and Permeability Fields to Multiwell Pressure Data

Stochastic fractal (fGn and fBm) porosity and permeability fields are conditioned to given variogram, static (or hard), and multiwell pressure data within a Bayesian estimation framework. Because fGn distributions are normal/second-order stationary, it is shown that the Bayesian estimation methods based on the assumption of normal/second-order stationary distributions can be directly used to generate fGn porosity/permeability fields conditional to pressure data. However, because fBm is not second-order stationary, it is shown that such Bayesian estimation methods can be used with implementation of a pseudocovariance approach to generate fBm porosity/permeability fields conditional to multiwell pressure data. In addition, we provide methods to generate unconditional realizations of fBm/fGn fields honoring all variogram parameters. These unconditional realizations can then be conditioned to hard and pressure data observed at wells by using the randomized maximum likelihood method. Synthetic examples generated from one-, two-, and three-dimensional single-phase flow simulators are used to show the applicability of our methodology for generating realizations of fBm/fGn porosity and permeability fields conditioned to well-test pressure data and evaluating the uncertainty in reservoir performance predictions appropriately using these history-matched realizations.     

Comparison between neuro-fuzzy and fractal models for permeability prediction

We have used different techniques for permeability prediction using porosity core data from one well at the Maracaibo Lake, Venezuela. One of these techniques is statistical and uses neuro-fuzzy concepts. Another has been developed by Pape et al. (Geophysics 64(5):1447–1460, 1999), based on fractal theory and the Kozeny–Carman equations. We have also calculated permeability values using the empirical model obtained in 1949 by Tixier and a simple linear regression between the logarithms of permeability and porosity. We have used 100% of the permeability–porosity data to obtain the predictor equations in each case. The best fit, in terms of the root mean-square error, was obtained with the statistical approach. The results obtained from the fractal model, the Tixier equation or the linear approach do not improve the neuro-fuzzy results. We have also randomly taken 25% of the porosity data to obtain the predictor equations. The increase of the input data density for the neuro-fuzzy approach improves the results, as is expected for a statistical analysis. On the contrary, for the physical model based on the fractal theory, the decrease in the data density could allow reaching the ideal theoretical Kozeny–Carman model, on which are based the fractal equations, and hence, the permeability prediction using these expressions is improved.     

Holocene palaeogeographical reconstruction and relative sea-level changes in the southeastern part of the island of Samos (Greece)

In this paper, we focus on the southeastern coastal zone of the island of Samos (east-central Aegean Sea), in order to reconstruct the evolution of coastal landscapes and the relative sea-level changes during the late Holocene. We use geomorphological mapping, sedimentological and palaeontological proxies of late Holocene coastal deposits from two lagoon environments. We further compare our results with previously published sea-level data and we show that the southeastern part of Samos was characterized by a subsidence trend at least during the late Holocene, with RSL rise rates of ∼0.8 mm/yr. Our study additionally highlights that local-scale tectonics is responsible for the evolution of the coastal zone of Samos.     

水文物探技术的发展和应用

文章回顾与阐述了水文物探的找水,管水以及治水发展３个阶段,并列举出了水文物探的１０个方面应用成果及实例,同时,也对今后水文物探的技术开发与技术推广做了有关介绍。     

Bias in estimating fractal dimension with the rescaled-range (R/S) technique

Fractal geostatistics are being applied to subsurface geological data as a way of predicting the spatial distribution of hydrocarbon reservoir properties. The fractal dimension is the controlling parameter in stochastic methods to produce random fields of porosity and permeability. Rescaled range (R/S)analysis has become a popular way of estimating the fractal dimension, via determination of the Hurst exponent (H). A systematic investigation has been undertaken of the bias to be expected due to a range of factors commonly inherent in borehole data, particularly downhole wireline logs. The results are integrated with a review of previous work in this area. Small datasets. overlapping samples, drift and nonstationariry of means can produce a very large bias, and convergence of estimates of H around 0.85–0.90 regardless of original fractal dimension. Nonstationarity can also account for H>1, which has been reported in the literature but which is theoretically impossible for fractal time series. These results call into question the validity of fractal stochastic models built using fractal dimensions estimated with the R/Smethod.     

Bias in estimating fractal dimension with the rescaled-range (R/S) technique

Fractal geostatistics are being applied to subsurface geological data as a way of predicting the spatial distribution of hydrocarbon reservoir properties. The fractal dimension is the controlling parameter in stochastic methods to produce random fields of porosity and permeability. Rescaled range (R/S)analysis has become a popular way of estimating the fractal dimension, via determination of the Hurst exponent (H). A systematic investigation has been undertaken of the bias to be expected due to a range of factors commonly inherent in borehole data, particularly downhole wireline logs. The results are integrated with a review of previous work in this area. Small datasets. overlapping samples, drift and nonstationariry of means can produce a very large bias, and convergence of estimates of H around 0.85–0.90 regardless of original fractal dimension. Nonstationarity can also account for H>1, which has been reported in the literature but which is theoretically impossible for fractal time series. These results call into question the validity of fractal stochastic models built using fractal dimensions estimated with the R/Smethod.