24个甘蔗组合早代重演力和预测力分析

为研究甘蔗遗传特点和育种潜力,对常用的29个甘蔗亲本24个组合的7个性状进行重演力测试并进行相关分析和回归分析。结果表明,相关系数(r)和回归系数(b)都达到显著水平的性状有茎径、有效茎、锤度和单茎重,说明这些性状受环境影响较小,在甘蔗育种早期世代根据这一结果制订相应的选择标准,增大选择压力,可提高甘蔗育种效率。29个亲本中表现较好的亲本是ROC24、粤糖91-976、ROC1、ROC22,24个组合中综合性状较好的是ROC24×粤糖91-976、ROC1×ROC22、粤糖89-113×ROC22,在今后育种计划中可广泛利用。

甘蔗高生物量性状表现的重演力分析

通过５×３不完全双列杂交的甘蔗高生物量的１５个组合的有性世代和无性世代的大田栽培试验，分析了１５个组合８个性状的平均表现和重演力，结果表明：Ｃｏ１００１、Ｙａ９０－３３和ＣＰ７２－１２１０是较为理想的甘蔗高生物量育种的亲本。选１５×Ｙａ７３－２２６、选１５×Ｙａ８９－２６、选１５×Ｙａ９０－３３、Ｃｏ４１９×Ｙａ９０－３３、ＣＰ７２－１２１０×Ｙａ９０－３３是较好的甘蔗高生物量组合，在今后的甘蔗高生物量育种计划中应广泛地加以利用。重演力和预测力的分析进一步表明：株高、茎径、单茎重、小区产量、锤度、锤重、地上部鲜重的重演力较高，在早期世代应严加选择。而小区有效茎数的重演力较低，应放宽选择标准，以防漏选。

甘蔗杂交后代早期世代性状表达的重演力

以３×３ＮＣⅡ设计的９个组合的实生苗世代（ＳⅠ），实生苗宿根世代（ＳⅡＳＣ）和入选的单系新植（ＳⅡＰＣ）为材料，研究了ＳⅠ与ＳⅡＰＣ、ＳⅠ与ＳⅡＳＣ世代间７个重要经济性状的重演力。结果表明重演力在性状间、家系间有较大的差异；ＳⅠ与ＳⅡＳＣ间的重演力要比ＳⅠ与ＳⅡＰＣ间的重演力高；茎径的重演力最高而且稳定，在世代间可高度预测，可在ＳⅠ世代严加选择。其次株高的重演性也较强。有效茎数在ＳⅠ与ＳⅡＰＣ间重演性差，建议推迟到无性世代选择；在实生苗与其宿根世代，有效茎是一个高重演力的性状，说明宿根世代的有效茎数受实生苗世代的强烈影响，锤度的重演力中等偏低，在ＳⅠ世代表达不充分，建议适当放宽选择标准，以免优良基因型的遗失。ＲＯＣ１０×桂７３－１６７、ＣＰ６５－３５７×Ｙａ７３－５１２在ＳⅠ与ＳⅡＰＣ间性状的重演性好，ＣＰ７２－１２１０×桂７３－１６７、ＲＯＣ１０×桂７３－１６７、ＣＰ６５－３５７×Ｙａ８４－１５３在ＳⅠ与ＳⅡＳＣ间重演力强，家系在ＳⅠ与ＳⅡＰＣ、ＳⅠ与ＳⅡＳＣ的重演力好坏之间没有必然的联系。

Gravity inversion using the frequency characteristics of the density distribution

Three-dimensional gravity inversion based on the mass property model is very popular in recent years. The time and efficiency of inversion algorithms is relative to the magnitude of the target mesh. One approach is to search over the entire solution space for a more refined result. However, the inversion will be difficult with the increased parameters in the large search space and the number of computations increases exponentially. ｜n this paper, we propose a novel approach based on the frequency characteristics of the density distribution over the mesh. The purposes of our study are to reduce the parameters of three- dimensional gravity inversion and to lighten the image quality of the inversion result. The results show that the new method can expedite the inversion processing and get a better geological interpretation than tradition methods.

Extrapolated Tikhonov method and inversion of 3D density images of gravity data

Tikhonov regularization（TR） method has played a very important role in the gravity data and magnetic data process. In this paper, the Tikhonov regularization method with respect to the inversion of gravity data is discussed. and the extrapolated TR method（EXTR） is introduced to improve the fitting error. Furthermore, the effect of the parameters in the EXTR method on the fitting error, number of iterations, and inversion results are discussed in details. The computation results using a synthetic model with the same and different densities indicated that. compared with the TR method, the EXTR method not only achieves the a priori fitting error level set by the interpreter but also increases the fitting precision, although it increases the computation time and number of iterations. And the EXTR inversion results are more compact than the TR inversion results, which are more divergent. The range of the inversion data is closer to the default range of the model parameters, and the model features and default model density distribution agree well.

Parameter optimization of gravity density inversion based on correlation searching and the golden section algorithm

For density inversion of gravity anomaly data, once the inversion method is determined, the main factors affecting the inversion result are the inversion parameters and subdivision scheme. A set of reasonable inversion parameters and subdivision scheme can, not only improve the inversion process efficiency, but also ensure inversion result accuracy. The gravity inversion method based on correlation searching and the golden section algorithm is an effective potential field inversion method. It can be used to invert 2D and 3D physical properties with potential data observed on flat or rough surfaces. In this paper, we introduce in detail the density inversion principles based on correlation searching and the golden section algorithm. Considering that the gold section algorithm is not globally optimized. we present a heuristic method to ensure the inversion result is globally optimized. With a series of model tests, we systematically compare and analyze the inversion result efficiency and accuracy with different parameters. Based on the model test results, we conclude the selection principles for each inversion parameter with which the inversion accuracy can be obviously improved.

Three-dimensional gravity inversion based on 3D U-Net++

The gravity inversion is to restore genetic density distribution of the underground target to be explored for explaining the internal structure and distribution of the Earth.In this paper,we propose a new 3D gravity inversion method based on 3D U-Net++.Compared with two-dimensional gravity inversion,three-dimensional(3D)gravity inversion can more precisely describe the density distribution of underground space.However,conventional 3D gravity inversion method input is two-dimensional,the input and output of the network proposed in our method are three-dimensional.In the training stage,we design a large number of diversifi ed simulation model-data pairs by using the random walk method to improve the generalization ability of the network.In the test phase,we verify the network performance by using the model-data pairs generated by the simulation.To further illustrate the eff ectiveness of the algorithm,we apply the method to the inversion of the San Nicolas mining area,and the inversion results are basically consistent with the borehole measurement results.Moreover,the results of the 3D U-Net++inversion and the 3D U-Net inversion are compared.The density models of the 3D U-Net++inversion have higher resolution,more concentrated inversion results,and a clearer boundary of the density model.

3D joint inversion of surface and borehole gravity data using zeroth-order minimum entropy regularization

Surface and borehole gravity data contain complementary information.Thus,the joint inversion of these two data types can help retrieve the real spatial distributions of density bodies.When a sharp boundary exists between an anomalous density body and its surrounding rock,the interface recovered by smooth inversion with Tikhonov regularization is not clear,leading to difficulties in the subsequent geological interpretation.In this work,we develop a joint inversion of surface and borehole gravity data using zeroth-order minimum entropy regularization.The method takes advantage of the complementary information from surface and borehole gravity data to enhance the imaging resolution of density bodies.It also produces a focused imaging of bodies through the zeroth-order minimum entropy regularization without requiring a preselection of a proper focusing parameter.We apply the developed joint inversion approach to three diff erent synthetic data sets.Inversion results show that the focusing inversion with the zeroth-order minimum entropy regularization provides a good description of the true spatial extent of anomalous density bodies.Meanwhile,the joint focusing inversion reconstructs a more reliable density model with a relatively high resolution when a density body is passed through by one or more boreholes.

Optimization algorithm for rapid 3D gravity inversion

The practical application of 3D inversion of gravity data requires a lot of computation time and storage space.To solve this problem,we present an integrated optimization algorithm with the following components:(1)targeting high accuracy in the space domain and fast computation in the wavenumber domain,we design a fast 3D forward algorithm with high precision;and(2)taking advantage of the symmetry of the inversion matrix,the main calculation in gravity conjugate gradient inversion is decomposed into two forward calculations,thus optimizing the computational efficiency of 3D gravity inversion.We verify the calculation accuracy and efficiency of the optimization algorithm by testing various grid-number models through numerical simulation experiments.

Improved preconditioned conjugate gradient algorithm and application in 3D inversion of gravity-gradiometry data

With the continuous development of full tensor gradiometer （FTG） measurement techniques, three-dimensional （3D） inversion of FTG data is becoming increasingly used in oil and gas exploration. In the fast processing and interpretation of large-scale high-precision data, the use of the graphics processing unit process unit （GPU） and preconditioning methods are very important in the data inversion. In this paper, an improved preconditioned conjugate gradient algorithm is proposed by combining the symmetric successive over-relaxation （SSOR） technique and the incomplete Choleksy decomposition conjugate gradient algorithm （ICCG）. Since preparing the preconditioner requires extra time, a parallel implement based on GPU is proposed. The improved method is then applied in the inversion of noise- contaminated synthetic data to prove its adaptability in the inversion of 3D FTG data. Results show that the parallel SSOR-ICCG algorithm based on NVIDIA Tesla C2050 GPU achieves a speedup of approximately 25 times that of a serial program using a 2.0 GHz Central Processing Unit （CPU）. Real airbome gravity-gradiometry data from Vinton salt dome （south- west Louisiana, USA） are also considered. Good results are obtained, which verifies the efficiency and feasibility of the proposed parallel method in fast inversion of 3D FTG data.

3D inversion of borehole gravity data using cokriging

Borehole gravity has been used in mineral exploration recently with the advent of slim-hole gravimeters. It is logical to perform inversion to utilize the information in the newly acquired data. The inversions were carried out by using cokriging,which is a geostatistical method of estimation that minimizes the error variance by applying cross-correlation between several variables. In this study the estimated densities are derived by using boreholes gravity and known densities along the borehole. This method does not need iterative process and computes efficiently. The selection of examples demonstrates that this method has the ability to include physical property from borehole measurements in the inversion. The synthetic examples demonstrate the density variation along a borehole can be well determined without depth constraints in the inversion. The resolution of the recovered model can be further improved by including the densities along the borehole for inversion. However,this capability decreases dramatically with the increasing of distance between the anomalous body and the borehole.

The distribution of deep source rocks in the GS Sag:joint MT-gravity modeling and constrained inversion

The coal-bearing strata of the deep Upper Paleozoic in the GS Sag have high hydrocarbon potential. Because of the absence of seismic data, we use electromagnetic （MT） and gravity data jointly to delineate the distribution of deep targets based on well logging and geological data. First, a preliminary geological model is established by using three-dimensional （3D） MT inversion results. Second, using the formation density and gravity anomalies, the preliminary geological model is modified by interactive inversion of the gravity data. Then, we conduct MT-constrained inversion based on the modified model to obtain an optimal geological model until the deviations at all stations are minimized. Finally, the geological model and a seismic profile in the middle of the sag is analysed. We determine that the deep reflections of the seismic profile correspond to the Upper Paleozoic that reaches thickness up to 800 m. The processing of field data suggests that the joint MT-gravity modeling and constrained inversion can reduce the multiple solutions for single geophysical data and thus improve the recognition of deep formations. The MT-constrained inversion is consistent with the geological features in the seismic section. This suggests that the joint MT and gravity modeling and constrained inversion can be used to delineate deep targets in similar basins.

3D density inversion of gravity gradiometry data with a multilevel hybrid parallel algorithm

The density inversion of gravity gradiometry data has attracted considerable attention;however,in large datasets,the multiplicity and low depth resolution as well as efficiency are constrained by time and computer memory requirements.To solve these problems,we improve the reweighting focusing inversion and probability tomography inversion with joint multiple tensors and prior information constraints,and assess the inversion results,computing efficiency,and dataset size.A Message Passing Interface(MPI)-Open Multi-Processing(OpenMP)-Computed Unified Device Architecture(CUDA)multilevel hybrid parallel inversion,named Hybrinv for short,is proposed.Using model and real data from the Vinton Dome,we confirm that Hybrinv can be used to compute the density distribution.For data size of 100×100×20,the hybrid parallel algorithm is fast and based on the run time and scalability we infer that it can be used to process the large-scale data.

Property Identification of Anomalous Seismic Bodies by GMES Techniques, A Case History

What are the anomalous seismic reflection bodies at depths of over 6000m？Are they reefs or igneous rock？This is a difficult problem for seismic techniques,but the GMES technique can handle it .The GMES technique is a joint exploration technique combining gravity,magnetic,electrical,and seismic techniques.The specific procedure is to conduct a 2D interface-constrained CEMP inversion using 2D seismic and log data followed by a property parameter inversion of the anomalous bodics using gravity and seismic data by the stripping technique.We then estimate the physical properties ofthe anomalous bodies,such as density,susceptibility,resistivity,velocity,and etc.to deduce the geological features of the bodies and provide a basis for drilling decisions.The work in the TZ area reported in this paper shows the applicability of the technique.

Application of gravity inversion focused in Changbai Mountain

Focusing inversion is accomplished by the iterative of abnormal source to make the image gradually focused. It can better reflect the underground geological geometry and physical parameters. The model experiments in the study show that gravity focusing inversion allows inversion image stabilization and polymerization,which solves the multiple solutions and instability of inversion and so on. The method is applied to measured gravity data processing of certain region of Changbai Mountain,compared to Euler deconvolution,the results show that the method for determining the horizontal position and depth of underground anomalies has good efforts.

Fast forward modeling of gravity anomalies for two-dimensional bodies of arbitrary shape and density distribution

A fast and high precision spatial domain algorithm is presented for forward modeling of two-dimensional(2D)body gravity anomalies of arbitrary shape and density distribution.The new algorithm takes advantage of the convolution properties of the expression for 2D gravity anomalies,uses a rectangular cell as a grid subdivision unit,and then 2D bodies with irregular cross-sections are approximated by a combination of 2D bodies with a rectangular cross section.The closed-form expression is used to calculate the gravitational anomalies of the combination of 2D bodies with a rectangular cross section.To improve computing effi ciency,the new algorithm uses a fast algorithm for the implementation of the Toeplitz matrix and vector multiplication.The synthetic 2D models with rectangular and circular cross-sections and constant and variable densities are designed to evaluate the computational accuracy and speed of the new algorithm.The experiment results show that the computation costs less than 6 s for a grid subdivision with 10000×10000 elements.Compared to the traditional forward modeling methods,the proposed method significantly improved computational effi ciency while guaranteeing computational accuracy.

Evaluating gravity gradient components based on a reweighted inversion method

In gravity gradient inversion,to choose an appropriate component combination is very important,that needs to understand the function of each component of gravity gradient in the inversion.In this paper,based on the previous research on the characteristics of gravity gradient components,we propose a reweighted inversion method to evaluate the influence of single gravity gradient component on the inversion resolution The proposed method only adopts the misfit function of the regularized equation and introduce a depth weighting function to overcome skin effect produced in gravity gradient inversion.A comparison between different inversion results was undertaken to verify the influence of the depth weighting function on the inversion result resolution.To avoid the premise of introducing prior information,we select the depth weighting function based on the sensitivity matrix.The inversion results using the single-prism model and the complex model show that the influence of different components on the resolution of inversion results is different in different directions,however,the inversion results based on two kind of models with adding different levels of random noise are basically consistent with the results of inversion without noises.Finally,the method was applied to real data from the Vinton salt dome,Louisiana,USA.

Joint inversion of gravity and multiple components of tensor gravity data

Geological structures often exhibit smooth characteristics away from sharp discontinuities. One aim of geophysical inversion is to recover information about the smooth structures as well as about the sharp discontinuities. Because no specific operator can provide a perfect sparse representation of complicated geological models, hyper-parameter regularization inversion based on the iterative split Bregman method was used to recover the features of both smooth and sharp geological structures. A novel preconditioned matrix was proposed, which counteracted the natural decay of the sensitivity matrix and its inverse matrix was calculated easily. Application of the algorithm to synthetic data produces density models that are good representations of the designed models. The results show that the algorithm proposed is feasible and effective.

Stress field evolution law of mining environment reconstructing structure with change of filling height

For improving global stability of mining environment reconstructing structure,the stress field evolution law of the structure with the filling height change of low-grade backfill was studied by ADINA finite element analysis code.Three kinds of filling schemes were designed and calculated,in which the filling heights were 2,4,and 7 m,separately.The results show that there are some rules in the stress field with the increase of the filling height as follows:(1) the maximum value of tension stress of the roof decreases gradually,and stress conditions are improved gradually;(2) the tension stress status in the vertical pillar is transformed into the compressive stress status,and the carrying capacity is improved gradually;however,when the filling height is beyond 2.8 m,the carrying capacity of the vertical pillar grows very slowly,so,there is little significance to continue to fill the low-grade backfill;(3) the bottom pillar suffers the squeezing action from the vertical pillars at first and then the gravity action of the low-grade backfill,and the maximum value of tension stress of the bottom pillar firstly increases and then decreases.Considering the economic factor,security and other factors,the low-grade backfill has the most reasonable height(2.8 m) in the scope of all filling height.

Modeling Evolution of Weighted Clique Networks

We propose a weighted clique network evolution model, which expands continuously by the addition of a new clique （maximal complete sub-graph） at. each time step. And the cliques in the network overlap with each other. The structural expansion of the weighted clique network is combined with the edges＇ weight and vertices＇ strengths dynamical evolution. The model is based on a weight-driven dynamics and a weights＇ enhancement mechanism combining with the network growth. We study the network properties, which include the distribution of vertices＇ strength and the distribution o~ edges＇ weight, and find that both the distributions follow the scale-free distribution. At the same time, we also find that the relationship between strength and degree of a vertex are linear correlation during the growth of the network. On the basis of mean-field theory, we study the weighted network model and prove that both vertices＇ strength and edges＇ weight of this model follow the scale-free distribution. And we exploit an algorithm to forecast the network dynamics, which can be used to reckon the distributions and the corresponding scaling exponents. Furthermore, we observe that mean-field based theoretic results are consistent with the statistical data of the model, which denotes the theoretical result in this paper is effective.