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  • 河北快三推荐号:Enhancing Reservoir Characterization

    后一万能码 2期内中 www.qgqx.net BroadSeis? extends the bandwidth to both high and low frequencies to deliver over 6 octaves of signal, with the best signal-to-noise ratio at low frequency. BroadSeis has been proven to be AVO compliant on both synthetic and real data, incorporating fully amplitude preserving deghosting algorithms to deliver true-amplitude, high-resolution subsurface images, reliable AVO attributes and stable, quantitative seismic inversion. As a consequence of the proprietary curved streamer configuration, BroadSeis is able to deliver the deepest tow in the industry, up to 50m to record low-noise ultra-low frequencies down to 2Hz. When combined with full source characterization and accurate 3D designature and debubbling, BroadSeis delivers stable low frequencies.

    Why does your seismic inversion work so well? Because low frequencies in CGG broadband are so good!"

    A major international oil company at Devex 2015

    Benefits from BroadSeis for Reservoir Characterization

    • BroadSeis is AVO compliant, receiver-ghost free wavelets deliver reliable AVO attributes
    • The low-noise low frequencies remove the need for log-derived low frequency models so that seismic inversion of BroadSeis data is therefore:
      • More reliable when well data are sparse
      • Less likely to yield biased estimates of absolute acoustic impedance
    • BroadSeis delivers Improved inversion quality and well ties
    • There is better delineation of thickness of gas-bearing zones with BroadSeis data
    • BroadSeis low frequencies reduce uncertainty in lithology prediction

    Improved Low Frequencies Remove the Need for Well Logs for Quantitative Inversion

    boats and spectra The lower frequencies provided by BroadSeis mean that a low frequency model derived from well logs is not required

    The broad bandwidth and ultra-low frequencies achieved using BroadSeis acquisition and processing, translate into more accurate and quantitative seismic inversion. The lack of low frequencies in conventional seismic data means that a low frequency model must be incorporated into the inversion process. With BroadSeis data, high-resolution NMO-derived seismic velocities are used to define the low frequency model in the 0-5 Hz range, while the reflectivity provides information from 2.5 Hz. BroadSeis low frequencies are also ideal for FWI (Full Waveform Inversion) which yields extremely detailed velocity models and so raises the frequency provided by the seismic velocities, and reduces the gap between reflectivity and velocity from the low end.  This means that quantitative inversion can be performed, even in areas without existing well information.

    Brazil acoustic inversion

    Case Study from Santos Basin

    In order to quantify the impact of the low frequency content on seismic inversion, the results of 3D acoustic inversion over a test area of around 1330 km2 over a Brazilian offshore field were compared for BroadSeis and conventional flat streamer data. The first target was the Eocene reservoir and the second the pre-salt carbonates. The objective was to see the difference in acoustic inversion results for conventional and BroadSeis seismic datasets, quantified by a blind well test, and to delineate the Atlanta reservoir. The test was executed with effort to synchronize all parameters of both inversions and see the result caused by the differences in the input data. The same initial model was used for both inversions and was created based on the logs from Well X with Vp (P-wave velocity) and density values being interpolated along basic horizons. A low-pass filter of 2-5Hz was applied to the model. All inversion parameters are based on Well X and Well Y was used as a blind test.

    Santos Basin wells

    The most obvious difference between them is that the broadband result shows much sharper borders of the pay interval of the reservoir (indicated by blue low impedance zones). The same effect can be seen on the vertical sections. The BroadSeis inversion defines the geometry of the reservoir better and decreases the uncertainty in calculating the reservoir volume. There is also better definition of geological bodies separated by faults, even where a fault is not included in the initial model, making interpretation easier and more reliable.

    The impedance from the BroadSeis inversion gives a better match to the “blind” well Y (below) – the inversion values are closer to the real log values because of the presence of low frequencies.

    Case Study from Northwest Australia

    In this example from northwest Australia, the inversion of BroadSeis data shows greater dynamic range and sharper boundaries than that from conventional data. There is an excellent tie with the well logs, which were not used in the inversion process. Both the conventional and BroadSeis inversions started from the same initial model.

    Conventional

    NWAusConvSeisWater saturation and impedance logs
    NWAConvIPImpedance
    NWAConvVPVSVp/Vs

     

    BroadSeis

    NWA BSeis SeismicWater saturation and impedance logs
    NWAusBSeisIPImpedance
    NWAus BSeis VpVsVp/Vs
    Pre-stack inversion of BroadSeis data from northwest Australia provides more
    quantitative estimates of elastic attributes.

    Lithology Prediction

    The elastic parameters derived from the seismic inversion were used to predict the lithology using LithoSI. In this technique, a supervised Bayesian classification is performed to produce probability cubes of the predicted lithology or rock properties.

    Crossplots of Ip and Vp/Vs

    Well Data
    NWAus LithoSI Well
    Conventional
    NWAus LithSI Conv
    BroadSeis
    NWAusLithoSIBSeis
    Crossplots of Ip and Vp/Vs from LithoSI lithology classification

    NWA Gas Sand ProbabilityCascaded LithoSI lithology classification using Ip and Vp/Vs from the inversion shows that
    BroadSeis provides a better match with lithology logs from the wells and reduces uncertainty
    in the prediction of the gas sands

    Gas Sand Probability

    The gas sand prediction from the BroadSeis data matches the well data much better than the conventional data. This indicates a considerable reduction in the uncertainty of the lithology prediction, which is also shown in the cross-section below, where the BroadSeis data gas prediction matches the well logs with a high degree of probability. Note that the BroadSeis data also indicates a high probability of gas sands in a discrete volume between wells A and B, which is not apparent on the conventional

     

    Variable Depth Streamer ? Benefits for Rock P...

    Loic Michel | Yves Lafet | Ronan Sablon | Damien Russier | R...
    ?2012 EAGE

    Experiencing the full bandwidth of energy fro...

    Jo Firth | Idar Horstad | Menne Schakel
    ?2014 EAGE

    Combining BroadSeis 3D HD-WAZ data in a reser...

    Gabino Castillo | Rob Mayer | Paola Fonseca | Maria Coronado...
    ?2015 EAGE
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  • 太坏了!傅欢遇“断子绝孙腿” 这动作红牌都不冤 2019-04-17
  • 市民工地发现并机智"抢回" 4件圆明园流散文物终"回家" 2019-04-17
  • 世界杯成中国企业营销升级大战场 2019-04-15
  • 中东部地区将有强降雨 京津冀等地有轻至中度霾 2019-04-11
  • 郑永年:新时代的清醒判断 2019-04-11
  • 让协商民主优势得以充分发挥 2019-04-10
  • 网友给太原市市长留言获回复 共计11条 2019-04-09
  • 尧都区车站街建设社区老党员高德宏同志手抄“党章”庆党生 2019-04-09
  • 正心正念 爱国爱教 佛界楷模 2019-04-02
  • 防治土地荒漠化 新疆保护生态兼顾农民增收 2019-04-02
  • 许倬云作序《现代的历程》:现代人的天问 2019-03-31
  • 证监会:首发审核政策始终没有变化 2019-03-31
  • 2008年全球金融危机之后,为什么金融危机发源地的美国,欧债危机重灾区的欧洲各国股市连续7年走牛,屡创历史新高,唯经济最好的中国股市却连续7年熊冠全球?去年中国 2018-11-17
  • 完成自己的第一部电影, 她23岁就做到了 2018-11-17