金山气田致密砂岩储层含气性叠前地震预测方法研究

松辽盆地金山气田致密砂岩储层物性较差、流体地震响应特征弱,储层含气性有效识别和预测是精细勘探开发的关键。基于叠前地震道集提高品质处理及入射角道集叠加处理,开展致密砂岩含气储层AVO响应特征分析,优选流体因子属性定性预测含气储层展布范围;基于致密砂岩含气储层岩石物理交会分析,寻找含气性敏感弹性参数,优选纵横波速度比参数开展叠前反演刻画含气储层展布规律,实现致密砂岩储层含气性的定量预测。实际应用研究表明,预测结果与实钻井符合率较高,对其他地区致密砂岩储层含气性预测研究具有借鉴意义。     

岩石物理建模技术在致密砂岩储层预测中的应用——以鄂尔多斯盆地北部H区块为例

岩石物理建模是叠前反演前重要的基础工作。以致密砂岩储层为目标,剖析了岩石物理建模涉及的主要过程。将测井评价与岩石物理建模视为迭代过程,测井评价提供岩石物理建模的输入数据,岩石物理建模控制测井评价参数的质量。在测井参数具有较高质量的情况下,优选岩石物理建模方法,优化关键参数,较为准确地预测了横波速度等弹性参数,为叠前弹性参数反演提供了可靠的基础数据。利用岩石物理解释模板对叠前反演纵横波速度体进行了解释,提高了致密砂岩气层的识别精度,在鄂尔多斯盆地取得了较好的应用效果。     

波形指示叠前地震反演方法在致密含油薄砂层预测中的应用

岩石物理研究的实践表明,叠前弹性参数及其多参数交会对储层和烃类更为敏感,以此为基础的叠前地震反演是定量预测含油气储层的有效方法。对于致密砂岩薄储层及其含油性预测而言,因其地震响应极其隐蔽、地震信号分辨率不足,目前普遍采用基于变差函数理论的高分辨率叠前随机反演方法,但其反演结果的高频成分随机性较强、可靠性降低,对预测结果的精度和可靠性造成较大的影响。为解决上述问题,以四川盆地中北部地区侏罗系沙溪庙组致密含油薄砂层的预测为例,在储层及含油性敏感弹性参数分析的基础上,开展了波形指示叠前地震高分辨率反演方法的应用研究。该方法利用叠前地震波形相似性代替传统变差函数优选测井样本,并以此进行随机模拟建立各弹性参数的初始模型;在贝叶斯框架下,联合初始模型、测井弹性参数先验概率分布和叠前同时反演弹性参数结果建立后验概率分布,对其进行Metropolis-Hastings采样得到收敛的平稳分布即为一个反演实现。实际应用效果表明,波形指示叠前地震反演方法能够从叠前地震资料中获取地层各项弹性参数的高分辨率宽频结果,且其高频成分的确定性增强,提高了致密砂岩薄储层及含油性的预测精度和可靠性。该项技术是陆相致密碎屑岩储层及含油气性高精度预测的有效方法,具有广阔的应用前景。     

基于叠前地震道集的流体因子同步反演方法

基于岩石物理理论建立的Gassmann流体因子能更好地区分多孔介质的流体和岩石基质,在储层预测及流体识别中获得了广泛地应用。现有技术中对常规叠前地震反演的弹性参数进行转换得到Gassmann流体因子的方法存在误差累计且预测精度不高。为此,建立一种Gassmann流体因子叠前地震道集反演方法,给出了叠前流体因子反演的目标泛函以及其梯度的解析解,为致密储层预测及流体识别提供重要参数。首先,综合考虑地震道集的数据匹配和流体因子的先验信息,建立先验信息约束的流体因子叠前反演目标泛函;然后,采用非线性最小二乘算法进行求解,对流体因子、剪切模量及密度进行同步联合反演。经过理论模型正演数据及井旁道集资料的反演应用,其结果表明,本文方法能够有效地反演流体因子,为从叠前地震资料挖掘更加丰富的地下介质信息提供了一种技术方法。     

叠前弹性参数反演及FFP分析技术在东海A气田开发中的应用

东海盆地西湖凹陷A气田主力储层为浅水三角洲分流河道沉积砂体,储层横向变化快,非均质性强,实施开发井存在较大风险,且目的层段砂岩与泥岩纵波阻抗值叠置,基于叠后地震的属性分析及纵波阻抗反演技术无法区分岩性和进行烃类检测。在岩石物理分析确定岩性和流体敏感弹性参数的基础上,基于叠前弹性参数反演技术对岩性进行预测,进而通过基于多个弹性参数的FFP(Facies Fluids Probabilities)分析技术对含油气砂岩概率进行定量预测。2项技术在A气田开发中取得了良好应用效果: 通过纵横波速比(v_p/v_s)参数反演,清晰刻画了主力层河道砂体形态,据此指导水平井优化并获得高达95%的高砂岩钻遇率; 通过v_p/v_s和纵波阻抗双参数联合的FFP分析技术预测了含气砂岩空间概率分布,据此预测了潜力气层并指导调整井成功挖潜。这2项技术对于东海油气田砂泥波阻抗叠置区的储层精细描述、油气潜力预测具有良好的推广应用价值。     

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。     

叠前多属性概率神经网络反演储层孔隙度

近十年来非线性反演方法(如人工神经网络、遗传算法)在地球物理解释中,得到越来越多的应用,但人工神经网络反演目前通常只采用叠后波阻抗反演结果和叠后地震属性(如振幅、频率和相位)进行预测,而忽略了地震叠前道集中包含的地层信息.这里通过叠前地震反演获得纵波、横波阻抗和密度信息,结合叠前地震属性,综合应用PNN神经网络方法来反演地层孔隙度参数.其过程包括:①提取叠前地震属性和叠前反演纵波、横波阻抗和密度参数;②分析孔隙度和各类叠前属性和叠前弹性参数的相关程度,确定出与孔隙度关系密切的主要参数;③综合叠前反演弹性参数和叠前属性等参数,应用神经网络分析方法反演得出孔隙度体.该方法克服了由于砂泥岩波阻抗重叠造成的叠后波阻抗反演储层预测存在多解性的问题,反演孔隙度体提高了储层识别精度,储层预测和钻井结果一致,符合实际地质规律,证明本方法正确有效.     

基于流体替代的敏感弹性参数优选及流体识别在渤海B油田的应用

叠前同时反演是目前储层流体识别的主要技术之一,但由于地下地质情况复杂及地球物理响应特征的多解性,仍然存在一定的不确定性。笔者从流体替代入手,分析地震振幅响应特征变化,利用流体评价因子定量筛选适合本区的流体敏感参数,最后通过叠前同时反演得到流体指示剖面。研究表明,在本区高孔隙度水层是影响油层识别的关键干扰因素,而λ/μ是适合本区的流体敏感参数,且实际应用表明该方法有效压制了强振幅水层,提高了流体识别精度。     

中江气田沙溪庙组河道砂岩储层定量预测

川西坳陷中江气田沙溪庙组河道砂体发育,但砂体发育特征复杂,且优质储层分布特征不明,有必要开展主要目的层河道砂体储层定量预测技术研究。在地震岩石物理分析的基础上,采用逐级控制的研究思路,首先综合采用多种地球物理技术开展目的层河道砂体展布刻画,然后基于叠后地质统计学反演技术实现岩性预测和孔隙度协模拟,最后在有利相带范围内实现了储层参数定量预测,且预测精度较高。结果表明,逐级控制的研究思路是取得可靠性预测结果的保障,地震岩石物理分析和地质统计学反演是主要关键技术。     

基于叠前多参数敏感因子融合的浊积岩储层识别技术

浊积岩油藏一直是济阳坳陷重要的勘探类型,经过多年勘探开发,目前面临的是“异质同像”型浊积岩,这类浊积岩的砂岩储层与非储层具有相近的速度、密度以及相似的地震波形特征,常规地震属性和叠后波阻抗识别难度大。由此建立了基于叠前多参数敏感因子融合的储层描述方法。该方法主要包含3个部分：(1)分析了影响横波估算精度的主要因素,建立了基于修正Xu-White模型的多矿物组分横波预测技术,提高了横波预测精度,为弹性参数的精准预测奠定基础;(2)提出了基于反射系数比的敏感因子定量评价方法,得到Murho、Lambrho和POIS这3个敏感弹性参数,应用3个弹性参数构建了敏感因子融合指数F,降低单参数的多解性,准确识别岩性;(3)开展叠前反演技术,反演敏感弹性参数,应用基于RGB三元色信息融合模型对3个敏感参数进行砂岩信息融合,实现岩性的精细预测。该技术在济阳坳陷坨71井区深水浊积岩油藏勘探中进行了应用,精细预测了研究区深水浊积扇体储层展布,预测结果与实钻井吻合度达到85%,提高了储层识别及描述精度。应用研究成果在该区描述砂体有利面积9.5 km~2,部署探井和开发井10余口,其中5口井完钻投产后均获工业...     

叠前反演方法在致密砂岩气储层预测中的应用

以鄂尔多斯东缘A区块为例,通过岩石物理正演分析,论证了储层岩石物理参数的敏感性,确定利用纵波阻抗与纵横波速度比参数进行储层的识别。在此基础上进行正演模拟,研究了地震的极限分辨率及不同厚度砂体的地震响应特征,确定了运用叠前地质统计学反演为核心的储层预测技术对该研究区太原组进行储层预测研究,以解决该区储层薄、横向变化快、单一岩石物理参数无法区分岩性等问题。地质统计学反演结果表明,该方法能有效的预测厚度大于3 m的储层。对比研究区内11口测井解释厚度与储层反演厚度表明,储层反演预测厚度平均误差为7.5%,其中5口盲井的平均误差为10.2%,一口新钻井的砂体厚度预测误差为1.73%,为该区的井位部署提供了可靠的资料参考。      

薄窄砂体地震跟踪预测方法

大庆长垣西部地区葡萄花油层主要发育水下分流河道和小片席状砂,砂体厚度1~3 m,横向变化快,分布零散,地震储层预测精度受到限制,给油藏评价和开发带来较大风险。为了提高薄窄砂体预测精度,以古龙油田为例,提出了分步逐级井震联合反演方法:以岩石物理响应特征分析为基础,优选反演方法,优化流程参数,不断增加滚动井数,通过5批161口开发井的优选及调整,砂体预测精度不断提高,确保了该油田初步开发方案实施效果,形成了可以推广应用的滚动预测跟踪调整的工作流程。     

Importance of coloured inversion technique for thin hydrocarbon sand reservoir detection – A case in mid Cambay basin

Cambay basin is an intra-cratonic rift graben formed as a result of rifting which was occurred in late Cretaceous with Deccan lava eruption through linear trending NNW to SSE directional basin. The Deccan basalt forms the basement over which more than 7–11 km thick piles of Tertiary sediments have been deposited during syn-rift and post-rift phases of basin development. Cambay basin has been considered as one of the significant hydrocarbon prolific basin in India. The biggest challenge in current days for this basin is further exploration or exploration under development stage in small marginal field or unexplored left out areas in the basin part as most of the areas are already explored/discovered by various small to big E&;P (exploration &; production) industrial players. In this present study one such small marginal field has been chosen for “Exploration under Development” portfolio in mid Cambay basin. The amount of oil-in-place volume, investment and techno-economics analysis of small marginal field has made this study area. In view of further hydrocarbon exploration in this area this kind of study will provide a robust support in limited dataset. The reservoir sand quality of the study area is discrete, thin and less permeable. This kind of sand body detection through classical seismic interpretation approach is difficult and there will be always a big amount of uncertainties for findings the pay reservoir sand. In view of the limitation of available data and challenging geological setup of the reservoir, a quantitative approach has been taken to detect the thin reservoir sand in this study area. Primarily coloured inversion technique has been applied on post-stack seismic data based upon well to seismic correlation and reservoir sand detection in seismic interpretation and well log property analysis. This technique has produced higher detectability impedance/property volume with respect to normal post-stack seismic data signature. Based on high contrast impedance/elastic property further seismic based attribute analysis on reservoir section has been performed. The attribute analysis has been made along surface and 3D seismic data level, provided clear image about the thin hydrocarbon sand reservoir. Based upon quantitative interpretation approach coloured inverted volume the prospect was chosen for further drilling in the study area and drilling of that sand was turned to be a hydrocarbon discovery prospect. The unconventional approaches e.g. coloured inversion with limited dataset for this kind of small marginal field has potential to find the hydrocarbon.     

多属性反演技术在储层预测研究中的应用——以珠江口盆地陆丰A区中新统珠江组储层为例

珠江口盆地陆丰A区中新统珠江组中-下段2370层是该地区主力油层之一, 但储层厚度差异大、分布不清, 严重制约了区域勘探部署.本文综合地震、测井和地质资料, 分析得出纵波阻抗和V_P/V_S为研究区识别岩性的敏感参数, 并通过叠前同步反演技术刻画出研究区2370层砂岩分布特征, 整体呈北厚南薄的展布.以地震振幅、分频属性及叠前反演属性为基础, 利用多属性反演技术分析统计了各属性与孔隙度之间的关系, 优选出密度、V_P/V_S、地震导数、LR、V_P、25~30Hz地震分频6种属性为储层物性识别参数, 综合预测研究区2370层储层滨岸砂坝砂体孔隙度发育特征.多属性反演结果表明, 在研究区东北部、西部, 厚层的滩坝储集砂体的孔隙度发育, 普遍在18%以上; 而在中部和东部, 受滩间、坝间泥岩与滩坝砂的叠合区影响呈条带状分布, 孔隙度为10%~18%.预测结果与同期钻井的钻后结果基本一致, 预测成功率在75%以上.多属性反演技术在研究区的储层预测中表现出良好的有效性和实用性, 对类似地区的储层预测也具有借鉴意义.     

粘弹介质叠前四参数同步反演及应用

叠前地震资料中包含纵波速度、横波速度、密度和吸收衰减系数等弹性及粘弹性信息,其中吸收衰减属性对储层物性及流体性质尤为敏感。本文从粘弹介质精确Zoeppritz方程出发,基于介质分解理论通过公式推导及近似,建立了包含纵波速度、横波速度、密度和吸收衰减系数的纵波反射系数特征方程,利用贝叶斯反演框架,实现了叠前纵波速度、横波速度、密度、衰减四参数同步反演。模型与实际资料反演效果均表明了该方法的可靠性。该方法较好应用于胜利油田东部海上探区的油气识别,相比于常规弹性介质流体因子,四参数同步反演方法得到的吸收衰减系数能更准确地表征油气的分布。     

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.     

Discrimination of pore fluid and lithology of a well in X Field,Niger Delta,Nigeria

Quantitative rock physics analyses were used to determine the lithology and pore fluid of a reservoir in the Niger Delta. Inaccurate prediction of lithology and pore fluid results in the inaccurate determination of other petrophysical properties and parameters such as porosity, permeability, and net pay. This research is to predict lithology and pore fluid using rock physics analysis. However, reservoir zones were also predicted. Density, compressional wave velocity, and shear wave velocity logs were used as input to calculate elastic parameters such as velocity ratio, Poisson’s ratio, and bulk modulus. The calculated velocity ratio log was used to differentiate between sand and shale. Poisson’s ratio and velocity ratio using Goodway interpretation template were carried out and used to delineate pore fluid content, gas sand, oil sand, and sandstone formation from crossplot analysis.     

基于地质统计学反演方法的洛带气田储层预测

研究区域为洛带气田遂宁组,该储层具有厚度薄、低孔隙度、低渗透层等特征,单一的约束稀疏脉冲反演难以达到精确刻画有利相带。地质统计学反演适用于复杂储层的地震预测和描述,与常规波阻抗反演相比,具有较高的垂向分辨率,能更有效地反映厚度薄的储层,反演结果更接近实际地质特征,能够很好地弥补约束稀疏脉冲反演缺陷,实现对储层特征的精细描述。针对研究区地质特点,根据储层发育特征和地质规律,基于地质统计学理论,采用岩性划分及统计学参数分析等技术方法进行储层预测,有效地预测了洛带气田的砂体厚度、平均孔隙度平面以及储层厚度。     

Integrated Reservoir Characterization and Petrophysical Analysis of Cretaceous Sands in Lower Indus Basin,Pakistan

The reservoir character of the Cretaceous sand is evaluated in Lower Indus Basin, Pakistan where water flooding is very common. Thus, prediction of subsurface structure, lithology and reservoir characterization is fundamental for a successful oil or gas discovery. Seismic reflective response is an important tool to detect sub-surface structure. Seismic reflection response is not enough to highlight geological boundaries and fluids in the pore space therefore, the use of integrated approach is vital to map sub-surface heterogeneities with high level of confidence. Based on seismic character and continuity of prominent reflectors four seismic horizons are marked on the seismic sections. All the strata is highly disturbed and distorted with presence of a network of fault bounded horst and graben structures, which indicate that the area was under compressional tectonic regime. These fault bounded geological structure formed structural traps favorable for the accumulation of hydrocarbon. The petrophysical analysis reveals that the Cretaceous sand formation has four types of sand: Sand A, B, C and D with good porosity (15 % average) and low volume of shale. Although complete petroleum system is present with structural traps and reservoir character of sand interval is very good but these sands are highly saturated with water thus are water flooded, which is the main reason of the abundant wells in the study area.     

基于EI-Fatti弹性波阻抗反演的流体识别

通过EI-Fatti弹性波阻抗反演直接得到了纵波阻抗、横波阻抗和密度数据,并以三类AVO模型进行反射系数试算,满足了流体识别对反演精度较高的要求。同时,采用基于EI-Fatti弹性波阻抗的两个流体识别因子对三类AVO模型进行对比分析,表明两种流体识别因子对于不同类型的AVO模型的流体识别效果是不同的。在实际资料中,利用弹性波阻抗反演产生较多弹性参数的优势,将这些弹性参数与储层参数进行交会和相关分析,分别定性和定量地对储层进行流体识别,从而达到了有效区分高饱含气和低饱含气储层的目的。