AVO叠前反演在中等阻抗储层预测中的应用

新场气田须四下亚段TX94砂体为砂砾岩互层。前期勘探证实,砂岩为有效储层,由于砂岩与作为围岩的泥岩阻抗接近,而砾岩的阻抗又远远大于砂泥岩,常规地震属性及叠后反演无法准确识别砂岩。采用AVO叠前反演技术,综合应用纵波弹性阻抗和纵波、横波速度比,结合岩石物理模板,对砂岩进行了准确刻画。这里阐述了AVO叠前反演的原理,讨论了反演处理中的地震数据分析,岩石物理分析,子波提取,低频趋势模型建立等关键步骤。反演结果表明,AVO叠前反演能很好地识别砂岩,降低了勘探风险。     

利用岩性阻抗识别砂岩、泥岩以及砂体叠置——以北部湾盆地涠洲A油田为例

针对涠洲A油田储层平面非均质性强、存在砂体叠置,以及单纯的波阻抗反演不能十分有效地识别砂泥岩和叠置砂体,提出了将纵波阻抗与横波阻抗通过一定的数学变换获得岩性阻抗的方法,证实了该岩性阻抗反演结果与实钻井吻合程度高,有效区分了砂岩和泥岩,并成功地预测了涠洲A油田砂体叠置的关系。     

随机反演在陆丰13-1油田储层预测中的应用

这里以陆丰13-1油田为例,研究发现井上波阻抗曲线并不能有效区分砂岩储层和泥岩非储层,故对孔隙度数据体进行了反演.首先对井上孔隙度曲线进行直方图统计分析,变差函数分析及孔隙度和波阻抗的相关性分析,然后用高斯模拟加模拟退火的随机反演方法对研究区进行了孔隙度体的反演.经反演发现,较其它反演方法孔隙度体反演剖面分辨率有了很大提高,对薄砂体也能很好地识别,且与井上吻合较好,能很好地刻画出砂体的横向变化情况,平面上砂体的展布也符合该区的沉积相分布.     

反演技术在解决煤层顶板岩性应用中的几个重要环节

淮南矿区煤层为石炭二叠纪煤层,13-1煤属下石盒子组,煤层全区稳定,平均厚度为3．5m。由于该区视电阻率曲线在砂岩及煤层反映为高电阻率,而泥岩电阻率相对平缓,针对这个特点,利用约束稀疏脉冲反演方法,结合地震数据,重构富含顶底板砂泥岩信息的波阻抗曲线,得到了联井波阻抗剖面及煤层顶板属性切片图,该成果图可清晰反映13—1煤层及顶板以上10m范围内的砂、泥分布。通过该实例的应用,对如何建立地质模型、重构波阻抗的方法、子波估算方法及稀疏脉冲反演中的A值的选择等几个重要环节进行了剖析。     

河流砂岩地震储层预测中的几个问题

河流砂岩是陆相盆地常见储层类型及油气储集有利场所。由于河流改道迁移频繁,河流相沉积常为砂、泥岩交互且岩性横向变化快,造成地震反射呈断续特征,利用常规地震资料进行砂、泥岩分辨和预测难度很大。笔者在分析河流砂岩地质特征和地球物理响应的基础上,研究和讨论了砂岩的精确标定、等时地层格架下的精细解释和地震属性提取,优选地震振幅类属性和分频处理预测薄层砂岩的平面展布,构建合理的地质模型,优选参数进行拟声波反演预测砂岩垂向分布及厚度变化等储层预测中的技术问题。通过实际应用和资料验证,采用技术方法合理,并取得了高精度的预测结果。     

扩展弹性阻抗反演技术在致密砂岩薄储层含气性预测中的应用

与叠后反演相比,叠前弹性阻抗对储层或烃类更为敏感,而扩展弹性阻抗反演是一种利用振幅随偏移距变化来分析、识别岩性和含气性的有效方法技术。笔者论述了扩展弹性阻抗反演方法理论和反演关键技术、步骤,并针对鄂尔多斯盆地北部DND气田盒1、山2段典型致密砂岩气藏的含气预测,提出了一套融合技术思路进行横波估测,该方法将公式法、模型法和神经网络法结合,以便在砂岩段使用模型法估算,在泥岩段以公式法为低频约束,同时结合神经网络法来预测泥岩段横波信息,避免了Xu-White模型由于总孔隙度测量不准确造成的泥岩段预测误差。实际应用表明,该方法能够满足致密砂岩薄储层含气预测,准确地预测了含气砂体的展布情况,预测结果与实钻吻合率高达90%。     

渤海湾盆地歧口凹陷南部沙河街组浊积扇储层综合预测

渤海湾盆地歧口凹陷南部古近系沙河街组发育一套湖相浊积扇沉积,砂岩储层以分布范围小、变化快、砂泥岩薄互层发育为特点。基于层序地层格架和储层成因类型的认识,利用纵向精细的测井资料和横向密集的地震资料,综合开展地震属性分析、测井约束反演和地质统计反演"三步骤"储层预测。研究表明:顺物源方向砂体呈前积叠置,分布较连续;而垂直物源方向,砂体分布变化快,多呈透镜状分布。受浊积扇南部断层下降盘的控制,南部砂体总体上较厚,浊积水道砂体也相对较厚。应用效果表明:地震属性分析、测井约束反演和地质统计反演"三步骤"储层综合预测技术比较适合稀井网、大井距条件下的储层精细预测。     

利用井约束反演技术进行油藏描述研究

论述了一种针对薄互储层条件下的油藏描述方法，以井约束反演技术为基础，利用对岩性变化敏感的测井曲线进行井约束条件下的二维地震资料储层反演处理，大大提高了地震资料的分辨率，为砂泥岩薄互层储层预测奠定了基础。     

拟声波反演技术在识别煤层顶底板砂泥岩中的应用

当煤层顶底板为泥岩时,其煤层气含量一般较高。为预测煤层气富集区,通过地震资料和测井数据分析,基于纵波阻抗反演和拟声波阻抗反演技术的方法获得煤层顶底板位置和砂泥岩的分布规律,为煤层气勘探开发提供依据。首先由于煤层纵波阻抗值很低,可在纵波阻抗反演剖面中准确获得煤层顶底板位置;其次利用自然伽马曲线构建拟声波曲线,在横向连续性强的拟声波阻抗反演剖面中,由于泥岩表现为拟声波阻抗高值,砂岩表现为低值,可通过数据分析得到砂泥岩值域范围;最后可以此为依据进行精细划分。实际应用表明,这种方法比传统纵波阻抗反演方法效果更好,分辨率更高。     

塔河油田3区石炭系超深薄层碎屑岩储层预测研究

针对塔河油田3区石炭系卡拉沙依组地震数据很难识别薄砂体的问题,对比分析了采用地震资料提频处理、分频处理、储层高分辨率敏感参数反演等不同手段得到的储层预测结果,筛选出高分辨率储层敏感参数反演作为卡拉沙依组砂泥岩段储层主要预测手段。通过探讨砂泥岩对声波时差的响应,以及对比分析自然电位、自然伽马以及补偿中子孔隙度与声波时差的关系,确定自然电位与声波时差的相关性最好,由此选取自然电位作为最佳电性敏感参数参与高分辨率敏感参数反演预测。从井点、剖面、平面等方面检验和评价高分辨率储层预测成果,结果表明其反演预测效果较好,符合塔河油田3区石炭系的储层预测要求,实现了对石炭系主力砂体空间展布的解释与描述,建立了塔河油田3区石炭系卡拉沙依组储层模型。     

岩性反演在煤层顶板砂体识别中的应用

EXB矿区主要目的层为一套泛滥平原河流相含煤碎屑岩沉积地层,煤层顶板岩性空间变化快,预测难度大。针对该问题,本文利用测井岩石物理分析建立煤、中砂岩、细砂岩和泥质砂岩的波阻抗频率直方图:煤的波阻抗值较小,主要范围3 000~6 300 m/s·（g/cm3）;中砂岩的波阻抗值域范围5 500~10 000 m/s·（g/cm3）;由于细砂岩和泥质砂岩性质接近,在波阻抗上无法区分,将两者合并处理,值域范围6 000~12 000 m/s·（g/cm3）。然后利用叠后地震反演计算波阻抗体,利用岩相与流体概率分析技术预测煤层顶板岩性的空间展布。结果表明,地震预测的岩性及其厚度的宏观变化趋势与钻井揭示结果基本一致,岩性平面厚度分布规律与沉积环境相符。      

万昌地区永二段水下滑塌扇内上倾尖灭砂体识别

上倾尖灭型油气藏是岩性油气藏的基本类型之一.对上倾尖灭砂体的识别是岩性油气藏勘探的任务之一.在对比单一利用地震资料、地震属性和波阻抗反演等方法进行砂体识别的优缺点后, 提出运用波阻抗和瞬时相位相叠合的新方法对砂体进行识别.运用此方法, 对万昌地区水下滑塌扇内部上倾尖灭砂体进行了精细解释和分析.得出以下结论: (1)通过钻井岩心识别沉积相类型, 结合均方根振幅属性和同沉积断层分布情况, 可以准确地确定伊通盆地万昌地区永二段水下滑塌扇的分布范围; (2)用波阻抗和瞬时相位属性联合的方法对水下滑塌扇内部上倾尖灭砂体进行识别取得了较好的效果, 万昌地区WC1井附近水下滑塌扇内至少有两期最具油气勘探价值的上倾尖灭砂体.      

鄂尔多斯盆地东部上古生界煤系页岩气藏特征及勘探方向

煤系页岩气是未来非常规天然气的勘探方向。以鄂尔多斯盆地东部为例,对区内上古生界煤系太原组和山西组页岩气成藏的构造条件、储层特征和资源潜力进行了分析。研究认为,区内构造简单,泥页岩储层埋藏浅,厚度大,泥页岩有机质演化程度较高,有机碳含量较高,页岩气含量较高,页岩气成藏条件较优越,页岩气勘探开发的有利区位于府谷-神木-临县一带。鄂尔多斯盆地东部上古生界煤层发育,煤层气含量较高,局部层段存在砂岩气,页岩气可与煤层气、煤系砂岩气等综合勘查、共同开发。      

Estimation of petrophysical parameters using seismic inversion and neural network modeling in Upper Assam basin,India

Estimation of petrophysical parameters is an important issue of any reservoirs. Porosity, volume of shale and water saturation has been evaluated for reservoirs of Upper Assam basin, located in northeastern India from well log and seismic data. Absolute acoustic impedance (AAI) and relative acoustic impedance (RAI) are generated from model based inversion of 2-D post-stack seismic data. The top of geological formation, sand reservoirs, shale layers and discontinuities at faults are detected in RAI section under the study area. Tipam Sandstone (TS) and Barail Arenaceous Sandstone (BAS) are the main reservoirs, delineated from the logs of available wells and RAI section. Porosity section is obtained using porosity wavelet and porosity reflectivity from post-stack seismic data. Two multilayered feed forward neural network (MLFN) models are created with inputs: AAI, porosity, density and shear impedance and outputs: volume of shale and water saturation with single hidden layer. The estimated average porosity in TS and BAS reservoir varies from 30% to 36% and 18% to 30% respectively. The volume of shale and water saturation ranges from 10% to 30% and 20% to 60% in TS reservoir and 28% to 30% and 23% to 55% in BAS reservoir respectively.     

Cyclicity in early Permian fluviatile Gondwana coal measures: An example from Giridih and Saharjuri basins,Bihar, India

The Karharbari and Barakar coal measures of Giridih and Saharjuri basins of Bihar, eastern India, comprise an interbedded assemblage of sandstone, shale and coal in variable abundance. The lithofacies composition records a progressive decrease in sandstone and enrichment of shale and coal from Karharbari up to Barakar. Application of first-order embedded Markov-chain statistics to subsurface data of Karharbari (52 borehole logs) and Barakar (10 borehole logs) reveals that deposition in both the coal measures followed a Markovian mechanism with variable probability, to yield a sequence of upward transition from sandstone through shale to coal. The repetitive fining-upward cycles are asymmetrical, i.e. sandstone → shale → coal → sandstone in the case of Karharbari, but symmetrical as sandstone → shale → coal → shale in Barakar.The abundance of sandstone and the asymmetrical nature of Karharbari cycles are attributed to abrupt shifting of channel bars in low-sinuosity anabranching streams. By contrast, the subequal amount of sandstone, shale and coal forming symmetrical cycles in the overlying Barakar Formation is due perhaps to a slow and gradual shift of the stream channels over and across the adjacent subenvironments of the flood plain.     

塔中Ⅲ区碳酸盐岩储层去泥质反演及泥质充填判别

塔里木盆地塔中Ⅲ区奥陶系碳酸盐岩储层是近年来勘探重点区域,良里塔格组储层内沉积泥质灰岩条带,以及一间房组洞穴顶部存在的沉积泥质条带,给储层预测带来了较大难度。为提高储层预测精度,分析奥陶系良里塔格组和一间房组储层内泥质展布规律,建立沉积泥质灰岩条带背景纵波阻抗体,完成了无井约束叠后地质统计学反演。研究结果表明,无井反演储层预测纵向发育位置、储层级别和已钻井吻合较好。利用叠前同时反演得到纵横波速比,通过纵波阻抗与纵横波速比交会图分析法,划分了一间房组优质储层、泥质充填储层、基质灰岩分布区间,对洞穴型储层泥质充填、叠前流体预测反演进行探索,确保储层预测的可靠性。     

综合物探在山东某矿井采区的应用

山东某勘探区内目的层为3#煤层，厚度1．65-3m，与围岩物性差异明显，能形成校强反射波，根据其地震数据波组特征、频谱特征等相关信息解释了3#煤层赋在状态风氧化带范围及断层分布规律等，并根据瞬变电磁资料，圈定了3#煤层顶扳砂岩富水带。     

Coupled accumulation characteristics of Carboniferous-Permian coal measure gases in the Northern Ordos Basin,China

The northern Ordos Basin provides a favorable geological environment for the accumulation and development of coal measure gases (CMG). The hydrocarbon generation potential and reservoir systems of the coal measures have been studied based on data from experimental tests and production and exploration wells, respectively. Further, the coupled accumulation characteristics were determined. The results show that the source rocks are characterized by favorable hydrocarbon generation potential, high thermal evolution (Ro%?=?1.3–2.3%), and mainly type III kerogen. Coals, typically aggregated organic matter, with a huge hydrocarbon generation potential (avg. 89.11 mg/g) and total organic content (TOC) (avg. 65.52%), are predominantly involved in gaseous hydrocarbon generation. Shales with good TOC contents (avg. 2.36%) and large cumulative thicknesses have an important role in gaseous hydrocarbon generation. Coal seams, shale layers, and sandstone layers occur as variably interbedded deposits, which form a favorable environment for CMG coupled accumulation. The porosity and permeability are ranked as follows: sandstone?>?coal?>?shale, with significant stress sensitivity and anisotropy. Two continuous gas generation peaks occurred in the Late Jurassic and Late Cretaceous, with an abundant amount of coal-derived and thermogenic gas generation, respectively. Potential gas-bearing sandstone layers can be formed by gas migration via short distances from nearby coal seams and shale layers. Coupled accumulation of CMG occurred in three stages: (1) stacked and interbedded reservoirs formation stage; (2) gas generating and charging stage; and (3) coupled accumulation adjustment stage. Coalbed methane (CBM)–tight sandstone gas (TSG) assemblage is a favorable target for CMG accumulation and development.