应用水平井信息提高地震反演精度

本文针对水平井的水平段信息无法直接应用到地震反演中的问题,以委内瑞拉地区从式水平井开发为主的A区块为例,提出水平井正演模拟与直井约束地震反演相结合,通过同位协同克里金融合的方法,实现水平段有效信息在地震反演中的应用,精细刻画了砂岩储层及薄泥岩隔夹层的空间分布,提高了地震反演体的预测精度与可靠性.研究成果应用到12口新开发井的井位设计和开发部署中,全部钻遇砂岩储层,砂岩厚度钻遇符合率为89%,泥岩隔夹层厚度钻探符合率达78%.应用水平井信息提高精度后的地震反演数据体为研究区重油项目的开发方式优化和后续储量复算提供了更为可靠的依据.     

伽马拟声波分频重构反演在储层预测中的应用

在地质和地震资料研究基础上,通过岩心、录井和测井分析,探索不同频率尺度测井曲线的储层意义,优选研究区内钻穿古近系底砂岩段砂泥薄互层储层5口探井的储层敏感曲线.在曲线预处理、标准化和敏感性分析的前提下,利用曲线分频拟合,对储层敏感曲线和声波曲线做小波多尺度分解,提取反映薄互层储层岩性变化的中频中尺度伽马曲线和反映地层速度的低频大尺度声波曲线.利用统计模型信息融合构建具有声波量纲的拟声波曲线.在地质研究和沉积演化模式的指导下,运用井约束反演的方法补充地震资料的高频和低频信息,提高地震资料的质量,预测有利储层分布.研究表明,伽马拟声波分频重构反演能有效的提高地震资料的纵向和横向分辨率,刻画复杂地质条件下的薄层储层分布.     

基于拟合随钻声波时差曲线的地震导向水平井技术

松辽盆地北部扶余油层是近几年致密油勘探的热点领域.针对平面展布窄小、厚度超薄储层的地震导向水平井问题,提出了基于拟合随钻声波时差曲线的地震导向水平井技术.其实现过程可概括为:(1)钻前利用已知直井拟合声波时差曲线,在此基础上开展纵波阻抗地质统计学反演,提高储层预测精度,优化井位轨迹设计;(2)钻探过程中目的层上方钻遇标志层(青山口组三套油页岩)时,调整时深转换参数,重新设计井轨迹;(3)钻头进入扶余油层,利用随钻伽马曲线阶段性拟合声波时差曲线,在此基础上开展动态拟纵波阻抗地质统计学反演储层及深度预测,指导井轨迹调整.通过对水平井Z的模拟分析,证明该方法可以有效导向水平井入靶、指导水平井钻进的同时,也能满足钻井现场的时效性要求.     

薄互储层地震反演方法在尼日尔Fana地区的应用

波阻抗反演是储层预测的主要方法之一.然而,当声波曲线和其计算出来的波阻抗不能很好地区分砂泥岩时,尤其是在研究区发育砂泥岩薄互储层的情况下,就会给储层预测带来困难.针对这一问题,本文以尼日尔Fana地区为例,采用声波测井曲线重构的方法进行测井约束反演,使储层的波阻抗特征更加明显.然后,对得到的波阻抗体作为输入进行神经网络岩性反演,结果精细刻画了研究区内砂体的空间分布和几何形态,提高了地震方法识别薄储集层的精度,指导了该区下一步勘探.     

基于背景驱动的储层弹性参数反演方法研究

本文为了解决低勘探程度区由于缺少测井资料而难以进行储层评价的难题,发展了背景驱动地震反演技术.该技术通过利用区块周边测井资料的背景驱动,克服了低勘探程度区块内因缺少测井资料而难以建模的难题.同时,该技术还规避了压实作用的影响,更有利于反演结果的解释.通过模型和实际数据测试,证明该方法具有较强的抗噪性,并且可以得到准确的反演结果,对低勘探程度区储层评价具有一定的参考价值.     

地震波形指示反演薄储层预测技术及其应用

盆地含油气区块从勘探评价进入开发阶段,随着产能任务的加大,钻井数量会越来越多,相应地对储层预测精度的要求也越来越高.地震波形指示反演从地震资料出发,以沉积规律和地震地质特征为指导,挖掘相同或相似沉积环境下测井曲线中蕴含的共性结构信息,进行地震先验有限样点模拟,通过蒙特卡罗模拟运算实现对薄储层的量化表征.反演运算过程充分体现了相控思想,较传统方法提高了运算效率和预测精度,可广泛应用于油气藏精细研究、油田开发过程和控制等,有助于最大程度地实现对油藏资源的开发和利用.     

碳酸盐岩地层孔隙度测井环境校正方法与应用

地震储层预测时需要高精度的测井数据,对测井曲线不仅在储层处要进行环境校正,而且在非储层处也要做环境校正。为了消除井眼扩径和其他影响因素对测井曲线的影响,针对声波和密度等孔隙度测井提出了一套校正办法。首先要找出测井曲线的失真,然后针对引起失真的原因,分别针对声波测井和密度测井提出具体校正办法,主要包括基于阵列声波测井的声波时差重新提取和其他资料的重构-编辑法。上述方法在川东北碳酸盐岩区块进行了实验,经分析与对比,证明该方法是有效的,思路和方法对其他区块也有借鉴意义。     

重构反演在断陷盆地致密储层预测的应用——以海拉尔盆地贝中油田为例

为了最大限度提高断陷盆地致密砂砾岩储层预测精度,从5个方面详细阐述了地震重构反演关键技术流程——测井曲线预处理、地震合成记录制作、基于频率补偿曲线重构技术、基于模型地震反演和随机地震反演方法,以贝中油田南二段为例,完成致密砂砾岩储层预测研究.研究表明,该重构反演方法分辨率和预测精度显著提高,该方法达到了致密砂砾岩储层预测的要求.并在重构反演在油田实际应用主要体现以下两点:(1)指导沉积微相划分.采用井点定相、反演切片组形的思路,综合录井、测井岩电等资料,完成南二段主力小层沉积微相的绘制;(2)有效指导高效水平井位部署.为了降低钻井失利风险,提高砂岩钻遇率,最大限度优化井网,综合构造和储层预测结果,采用探评井转注优化方式,实行"四注一采"井网方式,在区内部署了阶梯式水平井X2-P1.并通过数值模拟方法,当注采井井距300 m,且采用压裂求产方法时,预测至含水98%时,该井初期最高日产17.9 m~3,累产油6.59×10~4 m~3,采出程度22.13%.为此,提出的重构反演方法可以作为致密砂砾岩刻画的有效技术手段,这对后续断陷盆地致密砂砾岩储层含油潜力挖潜提供了有利技术支撑.     

东营凹陷王庄--宁海地区馆陶组储层预测

在研究地质资料、测井资料的基础上,针对胜利油田王庄宁海地区馆陶组地层的变化特征规律,制定了新的储层预测技术方法.（1）精细构造技术研究：利用原始地震资料、地震道积分资料及小波分解资料,结合地质平面层序地层单元分析方法,划分出地质单元边界.（2）反演测井声波时差技术研究：利用地震小波变换属性、测井声波时差资料,采用稳健回归方法直接反演声波时差,进而计算孔隙度.该方法,可提高反演的分辨率,增加了反演结果的可靠性.结合研究区地质资料,把这种研究技术方法应用到王庄宁海地区馆陶组储层的预测研究,取得了良好的效果.     

基于贝叶斯理论的多尺度地震反演方法

典型沉积旋回的模型分析表明,薄层调谐作用的影响抑制了地震相对高频的反射能量,降低了地震资料的分辨率.基于该资料的常规地震反演难以识别较薄的储层.为了提高地震反演的分辨率,本文利用小波变换分频技术,将地震资料分解为大、中、小三个尺度的数据体,有效减弱了调谐作用,增强了地震资料的相对高频和相对低频,提高了分辨率.在贝叶斯理论框架下,依据地震资料与沉积层序体的多尺度对应关系,逐级进行地震反演,把大尺度地震反演结果作为中尺度地震反演的模型约束,中尺度反演结果又作为小尺度地震反演的模型约束,最终完成整个反演.理论模型试算展示了该方法的逐级寻优特性,实际地震资料的多尺度反演表明,同常规稀疏脉冲反演方法相比,基于贝叶斯理论的多尺度反演对较薄储层的识别能力有实质性提升.     

SCIENCE CHINA Earth Sciences SUBJECT INDEX TO VOLUME 57(2014)

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Distribution of throughfall and stemflow in multi‐strata agroforestry,perennial monoculture,fallow and primary forest in central Amazonia,Brazil

The partitioning of rain water into throughfall, stemflow and interception loss when passing through plant canopies depends on properties of the respective plant species, such as leaf area and branch angles. In heterogeneous vegetation, such as tropical forest or polycultural systems, the presence of different plant species may consequently result in a mosaic of situations with respect to quantity and quality of water inputs into the soil. As these processes influence not only the water availability for the plants, but also water infiltration and nutrient leaching, the understanding of plant effects on the repartitioning of rain water may help in the optimization of land use systems and management practices. We measured throughfall and stemflow in a perennial polyculture (multi‐strata agroforestry), monocultures of peach palm (Bactris gasipaes) for fruit and for palmito, a monoculture of cupuaçu (Theobroma grandiflorum), spontaneous fallow and primary forest during one year in central Amazonia, Brazil. The effect on rain water partitioning was measured separately for four useful tree species in the polyculture and for two tree species in the primary forest. Throughfall at two stem distances, and stemflow, differed significantly between tree species, resulting in pronounced spatial patterns of water input into the soil in the polyculture system. For two tree species, peach palm for fruit (Bactris gasipaes) and Brazil nut trees (Bertholletia excelsa), the water input into the soil near the stem was significantly higher than the open‐area rainfall. This could lead to increased nutrient leaching when fertilizer is applied close to the stem of these trees. In the primary forest, such spatial patterns could also be detected, with significantly higher water input near a palm (Oenocarpus bacaba) than near a dicotyledonous tree species (Eschweilera sp.). Interception losses were 6·4% in the polyculture, 13·9 and 12·3% in the peach palm monocultures for fruit and for palmito, respectively, 0·5% in the cupuaçu monoculture and 3·1% in the fallow. With more than 20% of the open‐area rainfall, the highest stemflow contributions to the water input into the soil were measured in the palm monocultures and in the fallow. Copyright © 1999 John Wiley & Sons, Ltd.     

A Monte Carlo study of rainfall forecasting with a stochastic model

A procedure for short-term rainfall forecasting in real-time is developed and a study of the role of sampling on forecast ability is conducted. Ground level rainfall fields are forecasted using a stochastic space-time rainfall model in state-space form. Updating of the rainfall field in real-time is accomplished using a distributed parameter Kalman filter to optimally combine measurement information and forecast model estimates. The influence of sampling density on forecast accuracy is evaluated using a series of a simulated rainfall events generated with the same stochastic rainfall model. Sampling was conducted at five different network spatial densities. The results quantify the influence of sampling network density on real-time rainfall field forecasting. Statistical analyses of the rainfall field residuals illustrate improvement in one hour lead time forecasts at higher measurement densities.     

Anthropogenic Eutrophication and Red Tide Outbreak in Lacustrine Systems of the Kashmir Himalaya

Red tide, a recurrent phenomenon has become conspicuous in several Kashmir lake ecosystems since 1991. The responsible organism (Euglena pedunculata), a rare flagellate rediscovered in the Kashmir Himalaya (Khan 1993) caused first and unprecedented red tide outbreak, constituting a maximum of 96% of resident numerical phytoplankton density in Dal Lake. At present, conflicting hypotheses exist on the generation of causal assemblage(s) imparting redness to waters: Jeeji Bai (1991) linked its origin to acid precipitation – a fallout of burning oil‐fields during the Gulf War – whilst Khan (1993) holds local factor(s) responsible. Field/experimental studies support the latter contention that the influx of untreated sewage, in unison with warm temperatures, high levels of PhAR, iron and interruption to hydrological flow‐pattern together with absence/or reduction in grazing activity created conducive environmental milieu for red tide outbreak. Dal Lake “red tide” drifted the bloom‐inoculum to other waters, including Lake Wular, where additional ecological niches were carved out, threatening the aesthetic value and biological diversity of Kashmir lakes. Ecological monitoring indicates frequent seasonal red tide occurrence in Dal Lake (including summer‐autumn event of 1998) which testifies its unabated eutrophication status. Further studies are needed on ecological adaptability and biogeographic distribution of this rare and unique red tide‐causing flagellate.