混合发酵产甲壳素酶发酵条件优化及粗酶部分性质研究

利用甲壳素作为唯一碳源从土壤中筛得的真菌d,与细菌s混合发酵,对其最适产酶条件、所产甲壳素粗酶的制取以及粗酶性质进行初步研究。结果表明,混合发酵产酶的能力与单独发酵相比显著提高,混合发酵最适培养基组分为(×10~(-2) g/mL):尿素1.0,K_2HPO_4 0.07,KH_2PO_4 0.03,MgSO_4 0.05,酵母粉0.5,甲壳素1.0,pH 5.5,接种量2%(体积分数),32℃,130 r/min培养72 h,500 mL锥形瓶培养基装量为100 mL。经过优化,发酵液中甲壳素酶活力从0.73 U/mL提升到1.19 U/mL。通过对粗酶性质初步的研究,发现该酶有较好的稳定性。     

Pore Structure and Permeability Characterization of High‐rank Coal Reservoirs: A Case of the Bide‐Santang Basin,Western Guizhou,South China

The methods of nuclear magnetic resonance(NMR)spectroscopy,mercury injection porosimetry(MIP),and gas-water relative permeability(GWRP)were used to reveal the pore structure and permeability characteristics of high-rank coal reservoirs in the Bide-Santang basin,western Guizhou,South China,to provide guidance for coalbed methane(CBM)exploration and exploitation and obtain direct insights for the development of CBM wells.The results indicate that the coal reservoirs in the study area are characterized by well-developed adsorption pores and poorly developed seepage pores.The bimodal NMR transverse relaxation time(T2)spectra and the mutation in the fractal characteristic of the MIP pore volume indicate poor connectivity between the adsorption pores and the seepage pores.As a result,the effective porosity is relatively low,with an average of 1.70%.The irreducible water saturation of the coal reservoir is relatively high,with an average of 66%,leading to a low gas relative permeability under irreducible water saturation.This is the main reason for the low recovery of high-rank CBM reservoirs,and effective enhanced CBM recovery technology urgently is needed.As a nondestructive and less time-consuming technique,the NMR is a promising method to quantitatively characterize the pores and fractures of coals.     

广西合浦清水江高岭土矿的矿物学研究

广西合浦清水江高岭土矿床属花岗岩蚀变型.在区域地质背景概况调查及矿区地质特征、矿石自然品级分布研究的基础上,在矿区内7个不同地点采集样品并分离提纯.样品的X射线粉晶衍射分析表明黏土矿物主要由高岭石和伊利石组成;热分析显示了矿物的相变过程;扫描电镜观察显示高岭石为片状;其化学成分以比较低的铁、钛含量为特征;漂白作用对黄色和红色黏土的白度改善非常明显,小于2μm的颗粒分布占80%左右.这些特征表明广西合浦清水江高岭土的品质优良,具有广阔的开发利用前景.     

基于扫描电镜和JMicroVision图像分析软件的泥页岩孔隙结构表征研究

孔隙发育特征是泥页岩储集能力评价的关键参数之一。扫描电镜观察法已普遍用于描述泥页岩的孔隙发育特征,但是目前文献中对泥页岩微孔隙类型划分比较混乱,孔隙结构特征参数的表征以定性描述为主,缺乏定量表征手段。本文选取了18个泥页岩样品为研究对象,通过氩离子抛光和高分辨率扫描电子显微镜图像观察,基于孔隙发育形态、位置及成因,对样品中不同孔隙进行类型划分;结合JMicroVision图像分析软件,应用泥页岩微孔隙描述技术和孔隙尺度分类统计技术,统计不同类型孔隙发育数量、孔径大小、面孔率、形状系数、概率熵等参数,对其分布特征进行评价。研究表明,晶(粒)间孔隙和有机孔隙比较发育,其次为晶(粒)内孔和晶间隙。不同类型孔隙其孔径分布以纳米级为主,不同类型孔隙分布较无序,其概率熵主要分布在0.5～0.7之间,对应的形状系数分布差异也较大。有机质孔隙的形状系数主要分布在0.6～0.7范围内,形状分布以椭圆形或近似圆形为主,晶(粒)间孔隙和晶(粒)内孔隙的形状系数主要分布在0.3～0.7,分析晶(粒)间孔隙和晶(粒)内孔隙形状系数分布特征主要是受原始孔隙形态、压实作用和溶蚀作用的影响。研究认为,SEM与JMicroVision相结合是定量研究不同类型微孔发育特征的有效手段,为研究微孔的形成和演化奠定了基础。     

铁细菌培养过程中低分子有机酸钠盐对含硫酸根铁矿物形成的影响

普遍存在环境中的低分子有机酸盐对氧化亚铁硫杆菌的矿化产物(施氏矿和黄钾铁矾等铁矿物)会产生影响,从而导致环境中有毒重金属迁移转化发生变化.本文探讨了低分子有机酸钠盐对铁细菌HX3成长过程中代谢产物铁矿物的影响,并利用XRD、FTIR、FESEM和EDS对形成的铁矿物进行了表征与分析.研究结果表明,低浓度低分子有机酸钠盐...     

Geochemical characterization of Cretaceous sandstones from the Southern Benue Trough,Nigeria

Geochemical studies of sandstones from the three lithostratigraphic successions in the southern Benue Trough of Nigeria were undertaken for a geochemical characterization of the sandstones, and to assess their strati-graphic and source evolution.Major and trace elements data were obtained from outcrop sandstone samples. The SIO2/Al2O2, Fe2O3/K2O ra-tios and CaO contents have been used to characterize the Cretaceous sandstones into Al-rich and high and low Fe2O3/K2O ratio sandstones. Results indicate that there are geochemical features that display stratigraphic trends across the succession from the Asu River Group, Eze-Aku Group to the proto-Niger Delta succession which may imply a discontinuous evolution from different source terrains of Precambrian and Mesozoic ages that supplied the sediments. The Asu River Group sandstones have lower SiO2, Al2O3, Fe2O3 and higher MgO; the Eze-Aku sand-stones have higher TiO2, CaO, alkalis and lower MgO while the proto-Niger Delta sandstones have higher SiO2, Al2O3, Fe2O3 and lower alkalis and CaO. These discontinuities signify the influence of tectonic impulses that af-fected the southern Benue Trough during the Cretaceous time. Changes in ratios of TiO2/Al2O3, Fe2O3, Cr and Zr suggest an increasingly mafic contribution to the depositional basin with time. The chemical index of alteration in-creases with time, possibly suggesting that a more intense weathering regime in the hinterland developed with time.     

地震多属性综合解释的支持向量机方法研究

能够同时对多种属性进行训练,具有优秀推广能力的支持向量机(Support Vector Machine,简称SVM)方法是进行高精度地震参数预测的有力保障。然而,支持向量机中用于构建回归估计函数的参数最优解很难确定。针对该问题,通过建立数学模型进行参数选择研究,总结出了参数ε、C、σ2对样本预测的影响规律。在此基础上提出了求取惩罚因子C和核参数σ2的权系数公式。结合提出的参数求取公式,利用支持向量机方法,以地震属性为输入向量对渤海SZ36-1油田的砂泥岩百分比和孔隙度进行了预测。结果表明,利用该方法对储层参数进行预测具有较高的预测精度;权系数公式的提出极大地缩短了构建回归估计函数所耗用的时间,简化了参数选取的难度。     

基于统计岩石物理模型的各向异性页岩储层参数反演

提出了各向异性页岩储层统计岩石物理反演方法.通过统计岩石物理模型建立储层物性参数与弹性参数的定量关系,使用测井数据及井中岩石物理反演结果作为先验信息,将地震阻抗数据定量解释为储层物性参数、各向异性参数的空间分布.反演过程在贝叶斯框架下求得储层参数的后验概率密度函数,并从中得到参数的最优估计值及其不确定性的定量描述.在此过程中综合考虑了岩石物理模型对复杂地下介质的描述偏差和地震数据中噪声对反演不确定性的影响.在求取最大后验概率过程中使用模拟退火优化粒子群算法以提高收敛速度和计算准确性.将统计岩石物理技术应用于龙马溪组页岩气储层,得到储层泥质含量、压实指数、孔隙度、裂缝密度等物性,以及各向异性参数的空间分布及相应的不确定性估计,为页岩气储层的定量描述提供依据.

     

矿井导水构造三维精细模型构建与转换技术

为了解决矿井导水构造精细刻画与三维地质模型灵活继承中存在的陷落柱内部岩石结构刻画不精细、多源数据融合不准确等技术问题,开展了矿井导水构造多源数据融合实体模型构建方法、精细模型构建过程与模型转换系统开发等方面的研究。基于数据融合分布式结构理论,采用地质数据耦合、实体模型耦合和构建模式耦合3个层次的耦合策略,建立一套水文地质勘探多源数据融合为三维地质实体模型的构建方法,通过多源异构地质数据标准化预处理、跟踪与分类、数据配准、关联与融合等4个关键步骤,构建矿井导水构造多源数据融合实体模型。在地质统计学研究的基础上,以陷落柱为例,提出“矿井精细导水构造模型”与“广域概略模型”的基本概念,同时构建了陷落柱广域概念模型与精细模型。根据SURPAC和FLAC^3D2种三维模型的属性与数据结构特点,提出了矿井导水构造SURPAC和FLAC^3D模型转换方法,利用JAVA语言和TCL语言研发了SURPAC-FLAC^3D模型转换系统,该系统同时支持本地、网络操作与多用户多台机器的远程控制,最终实现了导水构造实体耦合模型转换为FLAC^3D计算模型的目标,为矿山地质条件精细勘查与融合构建、矿山水害精准预测与防治提供技术支撑。     

Markov chain Monte Carlo algorithms for target-oriented and interval-oriented amplitude versus angle inversions with non-parametric priors and non-linear forward modellings

In geophysical inverse problems, the posterior model can be analytically assessed only in case of linear forward operators, Gaussian, Gaussian mixture, or generalized Gaussian prior models, continuous model properties, and Gaussian-distributed noise contaminating the observed data. For this reason, one of the major challenges of seismic inversion is to derive reliable uncertainty appraisals in cases of complex prior models, non-linear forward operators and mixed discrete-continuous model parameters. We present two amplitude versus angle inversion strategies for the joint estimation of elastic properties and litho-fluid facies from pre-stack seismic data in case of non-parametric mixture prior distributions and non-linear forward modellings. The first strategy is a two-dimensional target-oriented inversion that inverts the amplitude versus angle responses of the target reflections by adopting the single-interface full Zoeppritz equations. The second is an interval-oriented approach that inverts the pre-stack seismic responses along a given time interval using a one-dimensional convolutional forward modelling still based on the Zoeppritz equations. In both approaches, the model vector includes the facies sequence and the elastic properties of P-wave velocity, S-wave velocity and density. The distribution of the elastic properties at each common-mid-point location (for the target-oriented approach) or at each time-sample position (for the time-interval approach) is assumed to be multimodal with as many modes as the number of litho-fluid facies considered. In this context, an analytical expression of the posterior model is no more available. For this reason, we adopt a Markov chain Monte Carlo algorithm to numerically evaluate the posterior uncertainties. With the aim of speeding up the convergence of the probabilistic sampling, we adopt a specific recipe that includes multiple chains, a parallel tempering strategy, a delayed rejection updating scheme and hybridizes the standard Metropolis–Hasting algorithm with the more advanced differential evolution Markov chain method. For the lack of available field seismic data, we validate the two implemented algorithms by inverting synthetic seismic data derived on the basis of realistic subsurface models and actual well log data. The two approaches are also benchmarked against two analytical inversion approaches that assume Gaussian-mixture-distributed elastic parameters. The final predictions and the convergence analysis of the two implemented methods proved that our approaches retrieve reliable estimations and accurate uncertainties quantifications with a reasonable computational effort.