孕镶金刚石钻头钻进控制新方法的研究

在分析了目前常用钻进控制方法的基础上提出了钻进中应采用控每转进尺的钻进控制方式，并对部分孕镶金刚石大钻头和做钻头进行了室内钻进试验，由每转进尺ｈ和单位钻压每转进尺ｈ／ｐ得出不同岩石中不同钻头的合理每转进尺范围，且由ｈ／ｐ值对不同岩石进行的最佳钻头的选择。     

基于岩石力学特性和机械比能理论的钻头评价和优选

针对川西某构造的地质构造和地层特征,本文以井史资料和测井数据为基础,建立了地层强度参数和岩石力学参数剖面,得出了分布规律,即岩石强度和可钻性级值普遍较高,且变化趋势同弹性模量、粘聚力、内摩擦角等力学参数一致,在2500～2700 m地层达到峰值,而泊松比则相反,达到最低值。提出了基于岩石力学特性和机械比能理论的钻头评价和优选方法,得出了每段地层钻头的机械比能值,对已使用钻头的使用效果进行系统评价,发现采用的PDC钻头效果不理想,形成了牙轮钻头、孕镶钻头为主的钻头推荐方案,为工区钻井提速设计提供指导。     

多因素正交试验法优选孕镶金刚石钻头结构参数的试验研究

笔者通过测试豫西代表性岩石的主要物理机械性质和模拟微钻钻进试验测定钻头磨耗强度,机械钻速等指标,介绍了用正交试验法综合评价优选钻头结构参数的方法.      

塔东古城地区钻头优选及应用

针对大庆油田塔东区块古城地区地层含砾、岩石硬度大、85%以上井段采用牙轮钻进,导致深部地层钻速慢,钻头磨损严重等问题,在传统钻速预测方法基础上,引入钻头磨损、地层岩性、应用井深等相关参数,建立钻头破岩效率计算方法,并结合所钻遇的地层岩性、测井资料及钻头类型等,建立钻头优选模型,实现钻头选型定量化,提出了适用于古城地区的钻头序列推荐方案。现场成功应用5口井,单只钻头进尺和平均机械钻速均得到了很大的提高,实现了钻头优选提速提效的目的,为古城地区的高效钻井施工提供了重要的技术支撑。     

金刚石钻头的碎岩问题

阐述了金刚石钻头碎岩机理。提出岩石受钻头线载荷作用观点，并从碎岩机理出发，依钻头所受的外力、钻头结构及特点、岩石性质，推导出了钻头钻速公式。     

人造金刚石聚晶地质岩心钻头钻岩效果

70年代初，我国开始研究人造金刚石聚晶，同时探索其在岩心钻探中应用，并获得成功。聚晶地质钻头已形成系列、聚晶切削具形状增多，磨削比高达1：10万。聚晶钻头在钻进软至中硬岩石，钻进效果显著，钻头寿命最高达684.17米，绳索取心钻头提钻间隔高达57.81米／次。可替代硬质合金钻头，提高钻探经济效益。     

红河油田地层可钻性研究与钻头优选

红河油田水平井钻头适应性差、起下钻频繁,导致机械钻速低和钻井周期长,严重制约了钻井提速提效。通过对红河油田地层岩心进行室内可钻性实验,建立了该地区岩石可钻性与声波测井相关性数学模型,从而确定了岩石可钻性级值剖面。实验及计算结果表明,红河油田地层可钻性级别为3～6级,上部属于软地层,下部属于中硬地层。基于地层可钻性优选了PDC钻头,经现场试验与应用,平均单只钻头进尺、机械钻速大幅提高,大大缩短了钻井周期,达到了水平井钻井提速提效的目的。     

正交试验法在钻探工程中的应用

一、概述为了加快“孕镶金刚石钻头与岩石适应性”的研究工作，实钻试验采用正交试验法（又称正交设计法）。它是利用一种排列整齐的标准化了的“正交表”来安排和分析多因素试验的科学方法。利用它仅作较少次数的试验，便能在不同地层岩石中优选出与所钻岩石相适应的钻头技术参数和较佳钻进参数，得出较为明确可靠的生产条件和结论，达到提高技术经济效果的目的。这不仅能坚持科学打钻，还将进一步提高技术和管理水平，为勘探工作做出有益的贡献。     

利用灰色局势决策评价和优选金刚石钻头

利用灰色局热决策综合了评价了金刚石钻头的技术经济效益，结合近几年的钻探生产实践和科研成果，经验证和对比，为豫西地区优选钻头提供了参考，也可为其它地区钻头优选提借鉴。     

准噶尔盆地中部1区钻井优化设计研究

围绕钻井工程设计优化展开研究,论述了准噶尔盆地中部1区井身结构优化过程,提出了井身结构优化方案;建立了该区岩石可钻性剖面,结合钻头使用效果评价,推荐了钻头选型方案;介绍了该区钻井液体系优选及使用情况。形成了准噶尔盆地中部1区钻井设计优化方案,提出了后续研究方向。     

分水岭算法在电成像测井图砾石识别中的最优参数研究

基于电成像测井,将分水岭算法应用到电成像测井图砾石的识别中,分水岭算法在砾石识别应用中的参数选取直接影响到识别效果。针对分水岭算法识别砾石的各个步骤,选取不同的优化参数进行处理,对处理效果进行对比分析,最终确定分水岭算法识别砾石的最优参数,并对吉林王府断陷AA井、BB井和CC井三口井进行实际处理,得到很好的效果。     

Selection of sand models and identification of parameters using an enhanced genetic algorithm

Numerous constitutive models of granular soils have been developed during the last few decades. As a consequence, how to select an appropriate model with the necessary features based on conventional tests and with an easy way of identifying parameters for geotechnical applications has become a major issue. This paper aims to discuss the selection of sand models and parameters identification by using genetic algorithm. A real‐coded genetic algorithm is enhanced for the optimization with high efficiency. Models with gradually varying features (elastic‐perfectly plastic modelling, nonlinear stress–strain hardening, critical state concept and two‐surface concept) are selected from numerous sand models as examples for optimization. Conventional triaxial tests on Hostun sand are selected as the objectives in the optimization. Four key points are then discussed in turn: (i) which features are necessary to be accounted for in constitutive modelling of sand; (ii) which type of tests (drained and/or undrained) should be selected for an optimal identification of parameters; (iii) what is the minimum number of tests that should be selected for parameter identification; and (iv) what is the suitable and least strain level of objective tests to obtain reliable and reasonable parameters. Finally, a useful guide, based on all comparisons, is provided at the end of the discussion. Copyright © 2015 John Wiley & Sons, Ltd.     

Determining the optimal pumping duration of transient pumping tests for estimating hydraulic properties of leaky aquifers using global curve-fitting method: a simulation approach

Global curve-fitting method (GCFM) is regarded as an effective approach in hydrogeological parameter estimation, as it integrates and uses pumping data and water recovery data of a transient pumping test for parameter estimation. The impacts of pumping duration on hydrogeological parameter estimation by GCFM were investigated in the present study using 2 in situ pumping tests and 24 simulated transient pumping tests. Empirical formulas for determining the optimal pumping duration were derived. The study results suggest that pumping duration will have impacts on the accuracy of hydrogeological parameter estimation. When pumping duration is longer than a certain period, relative errors of hydrogeological parameter estimation keep relatively stable within an acceptable limit. Therefore, it is unnecessary to continue the pumping for a very long time after the groundwater level has become stable. When the change rate of drawdown over time (γ) in an observation well located within a distance of 100 m to the pumping well reaches 0.134, the pumping can be stopped. If there are more than one observation wells in a pumping test, the smallest γ value should be selected to determine the optimal pumping duration. This research is meaningful in the instruction of pumping tests, and will reduce test costs greatly.     

中国北方岩溶区优势面控水机理及优势参数的确定与应用

在地下水数值模拟过程中，由于介质的空间变异性大，水文地质参数的优分工至今仍是一个重要而又难以解决的问题，本文将非饱和带土壤中的优势流概念推广到岩溶裂隙介质中，系统地分析了形成优势流的优势结构面控水机理，结合中国北方岩溶特征提出了实际工作中优势参数分方法，并依据有限元方法进一步求解，实例计算表明：利用优势面分析方法可以确定参数最优分区，所计算结果与实际情况基本一致，该结论对地下水流数值模拟参数的识别提供一种新的途径，同时对中国北方岩溶区地下水优势流的研究地以及地下水资源的科学评价等具有重要的参考价值。     

大型抽水试验最优化设计研究

抽水试验最优化设计,是指针对一个具体的地下水系统优选出一个抽水试验设计,它使抽水试验的费用最小化,而试验所获资料能满足识别参数所要求的可靠性,它可以概化为一个非线性的混合整数规划问题,其决策变量是确定抽水井和观测井的位置及井数、抽水量和观测频率等,采用搜索算法求解了这一优化问题,得到了理论最优解,并进行了实例演算。     

Microstructural weathering of sedimentary rocks by freeze–thaw cycles: Experimental study of state and transfer parameters

The frost sensitivity of a rock is resulting from the combined action of processes linked to porous network characteristics (state parameters) and to the way water flows into this porous network (transfer parameters), our study was thus about the influence of these parameters on frost weathering of rocks. Sedimentary rocks often found on buildings (limestone and sandstone) and consequently submitted to temperature variations have been selected. State and transfer parameters have been measured for sample characterization and the follow-up of weathering during freeze–thaw cycles. The coupled influence of a state parameter (dynamic modulus of elasticity) and a transfer parameter (water permeability), i.e. between rock skeletal strength and voids connection, has thus been discussed.     

地震资料叠前时间偏移处理在徐庄煤矿西部采区的应用

在构造复杂、速度横向变化不大地区,叠前时间偏移地震资料处理已成为改善成像效果的一种有效手段。影响偏移成像效果有二：一是建立偏移速度场,二是精选偏移参数。在徐庄煤矿西部采区叠前时间偏移处理中,对影响偏移成像质量的三维克希霍夫积分叠前时间偏移参数进行了试验,选取其最佳偏移孔径、拉伸算子、反假频算子等参数。对比叠前时间偏移与叠后时间偏移效果可见,叠前时间偏移比叠后时间偏移具有较高的信噪比和分辨率,其解释的断点、断面清晰,归位准确。     

三相生物流化床处理啤酒废水

通过三相生物流化床处理啤酒废水的实验研究,探讨曝气量和水力停留时间对处理效果的影响,确定最佳曝气量为0.25 m³/h,最佳水力停留时间为1.5 h。在该实验条件下,COD_cr平均去除率在85％以上,生物浓度高达28.31 mg/L,生物膜活性强,同时反应器具有较强的抗冲击负荷能力。     

基于DEM数据的古沉积面的重建方法——以青藏高原东北缘青海贵德盆地为例

广泛使用的数字高程模型（DEM）数据使得古沉积面的恢复成为可能。以青藏高原东北缘的青海贵德盆地为例,分析对比了前人获取代表古沉积面地表露头样本数据的几种方法．提出了插值样本应选择露头中代表原始沉积地层的顶面点的优选方法,并提取了更新统地表露头顶面点的样本数据。通过分析样本的特征、比较插值的结果,选择了自然邻点法进行插值预测,重建了贵德盆地更新统的古沉积面。正确样本,最的提取加上合适插值算法的选择．优化了重建的古沉积面。     

Evaluation of complex petroleum reservoirs based on data mining methods

In this study, we introduce the application of data mining to petroleum exploration and development to obtain high-performance predictive models and optimal classifications of geology, reservoirs, reservoir beds, and fluid properties. Data mining is a practical method for finding characteristics of, and inherent laws in massive multi-dimensional data. The data mining method is primarily composed of three loops, which are feature selection, model parameter optimization, and model performance evaluation. The method’s key techniques involve applying genetic algorithms to carry out feature selection and parameter optimization and using repeated cross-validation methods to obtain unbiased estimation of generalization accuracy. The optimal model is finally selected from the various algorithms tested. In this paper, the evaluation of water-flooded layers and the classification of conglomerate reservoirs in Karamay oil field are selected as case studies to analyze comprehensively two important functions in data mining, namely predictive modeling and cluster analysis. For the evaluation of water-flooded layers, six feature subset schemes and five distinct types of data mining methods (decision trees, artificial neural networks, support vector machines, Bayesian networks, and ensemble learning) are analyzed and compared. The results clearly demonstrate that decision trees are superior to the other methods in terms of predictive model accuracy and interpretability. Therefore, a decision tree-based model is selected as the final model for identifying water-flooded layers in the conglomerate reservoir. For the reservoir classification, the reservoir classification standards from four types of clustering algorithms, such as those based on division, level, model, and density, are comparatively analyzed. The results clearly indicate that the clustering derived from applying the standard K-means algorithm, which is based on division, provides the best fit to the geological characteristics of the actual reservoir and the greatest accuracy of reservoir classification. Moreover, the internal measurement parameters of this algorithm, such as compactness, efficiency, and resolution, are all better than those of the other three algorithms. Compared with traditional methods from exploration geophysics, the data mining method has obvious advantages in solving problems involving calculation of reservoir parameters and reservoir classification using different specialized field data. Hence, the effective application of data mining methods can provide better services for petroleum exploration and development.