The Long Lake Oilfield in Canada is rich in oil sand resources and the horizontal well-assisted gravity drainage (SAGD) method is mostly used in the development of it. Time-lapse seismic matching inversion technology is an effective means to realize the dynamic monitoring of oil sand SAGD development. However, due to the unclear geophysical monitoring mechanism of oil sand SAGD development reservoirs, and the lack of logging data, it is limited to directly describe the dynamic development characteristics of oil reservoir steam chambers by time-lapse seismic matching inversion technology. Therefore, this paper applies a time-lapse seismic matching inversion technology based on temperature-sensitive petrophysical experiments to realize dynamic monitoring of oil sand SAGD development. Firstly, based on the oil sand temperature-sensitive petrophysical experiment, the petrophysical mechanism of oil sand SAGD development was clarified, and the traditional Gassmann equation was improved to establish a petrophysical model, and the logging data matching the seismic data was reconstructed; Secondly, through the time-lapse seismic matching inversion technology, the internal differences of the reservoirs caused by the development are finely characterized; finally, the inversion results are converted into temperature field data by using a temperature-sensitive petrophysical quantity version to characterize the dynamic characteristics of the steam cavity development. The application shows that the research results effectively guide the deployment of adjustment wells and tap the potential of remaining oil in Changhu Oilfield, reducing 18 inefficient wells.

Seismic inversion is one of the main methods for reservoir prediction by integrating logging and seismic information, but the rationality of the prediction results is heavily dependent on the initial model. For offshore oil fields, limited by the sparse and non-uniform distributed wells, the initial model obtained by mathematical interpolation is often deviated from the actual reservoir distribution, especially for the complex sedimentary environment case. Sedimentary facies control can solve this problem to a certain extent, but it is easily affected by the subjective understanding. In this paper, a seismic inversion technology based on self-facies-control low-frequency model is studied, which can make full use of the horizontal identification and spatial structure to constrain the ability of seismic data. Based on the self-facies-control initial model, the pre-stack geostatistical inversion is suitable for non-parallel structure reservoir, and the inversion results highlight the reservoir spatial structure. The method effectively improves the spatial structure resolution of the inversion result, and achieved the ideal application effect in the actual oilfield. The predicted coincidence of sand bodies with thickness greater than 12 m is more than 85%, and the average drilling rate of sandstone in the horizontal section of the horizontal well is 92.77%.

低渗储层成因及控制因素多样,相对高渗储层(甜点)分布规律复杂,储层非均质性强,预测难度大.常规的地球物理方法可以有效区分岩性,但对低渗储层中的甜点区并不能很好地进行甄别.这里以海上某辫状河三角洲沉积低渗油田为例,通过总结低渗油藏储层高低渗分布模式特点,在此基础上建立相应的机理模型,研究低渗储层中相对高渗条带的地震正演响应特征规律,并以此为基础进行敏感地震属性优选,最终开展相约束的两步法预测相对高渗条带分布规律,为油田开发井部署提供借鉴.

近年来,越来越多的潜山型油气藏被发现,由于埋深大、钻井少,导致研究难度较高.本文以渤海B气田为例,探讨仅有一口井钻遇基底潜山时,应如何利用地质思维合理猜测并建立潜山地质模式,为后续预测有利储层和部署井位提供重要依据.

地震驱动建模技术建立的地质模型能够保持原始地震响应特征.针对其建立的地质模型转化为油藏模型常规流程,基于岩石物理建模及地震正演模拟,研究地震信息在转化过程中的响应变化,从而使地球物理信息可以约束油藏模型建立的过程,进一步提升油藏模型的精度,为油藏数值模拟奠定基础.

H Oilfield in the Pearl River Mouth Basin mainly develops delta front deposits. Its reservoir thickness is thin, the lateral change is fast, and the understanding of lithologic boundary and sand body connectivity is not clear, which seriously restricts the efficient development of oil field. Seismic waveform indication inversion can fully use the lateral changes of seismic waveforms to carry out high-frequency component estimation, and establish the interpolation model which is more consistent with the sedimentary characteristics. This method has good inter-well prediction ability, and is particularly suitable for high-precision prediction of fast lateral changes, strong non-average, and thin interbedded sand and mudstone reservoirs. While for another method, seismic sedimentology, is to use the seismic attribute slice to describe the lateral distribution range and sedimentary characteristics of the reservoir under the guidance of isochronous stratigraphic framework. It has a good detection effect on the plane sedimentary characteristics of thin reservoir which cannot be resolved vertically. Combined with the above two methods, a set of technical processes for fine description and sedimentary characterization of marine thin sandstone reservoirs is formed and has achieved good application results in H Oilfield, meanwhile provides effective technical support for remaining oil prediction and potential tapping adjustment in the study area.

加拿大阿萨巴斯卡地区油砂储层内的侧积砂层和泥岩隔夹层发育,井间非均质性强,储层内岩性的空间精确刻画对蒸汽辅助重力泄油(SAGD)开发井部署至关重要,而井孔储层段的岩性识别是进行空间岩性研究的基础.目前该地区井孔岩性划分主要依据钻井取心数据,成本很高,如果使用常规测井曲线就能准确识别岩性,则可以降低生产成本.以该地区Kinosis工区为研究对象,采用了基于贝叶斯概率模型无监督学习的测井岩相分析方法,选用常规测井曲线数据,在主成分分析(PCA)基础上进行聚类分析,得到井位处的垂向岩相分布.综合测井曲线、测井解释结果、岩心照片等地质资料,对岩相结果进行统计分析和标定,确定储层内每个岩相的岩性特征和地质特征.应用结果表明,无监督学习测井岩相分析技术充分利用数据之间的内在关系,无需提供先验的岩性模型,结果更为客观;通过标定,岩相识别结果与取心数据吻合率高,展示了一种利用常规测井曲线预测油砂储层井孔岩性的较为经济的研究方法.

随着勘探开发的不断深入,新发现的中深层(埋深主要在2000 m以下)油气田日益增多(渤中19-6、蓬莱9-1等),勘探新发现油田的探明石油地质储量中古近系储量占比高达66％,对其进行精确的储层预测已成为油田有效开发的必然要求.渤海古近系为扇三角洲或辫状河三角洲沉积,储层纵横向变化快,井少且位置分布不均,地震资料品质低,砂泥岩纵波阻抗叠置,使得反演技术在渤海古近系中应用较少,制约了储层预测精细刻画的需求.这里基于精细地层格架的建立,通过古地貌分析,提取地震敏感属性,确定砂体沉积演化特征,并利用特征曲线重构建立敏感地震弹性参数,结合地震多属性约束建立低频模型,进行相控反演,降低因储层非均质性强,基础资料品质低引入的反演不确定性,进一步提升了古近系储层预测精度.

The oil-sand reservoirs in the Athabasca region of Canada are estuarine deposits affected by tides. The strata are inclined, and the interlayers are well-developed. Accurate spatial characterization of reservoirs and interlayers is the key for efficient oil-sand development. In this paper, we have used prestack Bayesian lithofacies classification technology to predict the spatial distribution characteristics of reservoirs and interlayers of oil-sand reservoirs. We first use log lithofacies data as a label, select lithofacies sensitive elastic parameters to make a lithofacies classification probability distribution crossplot, and then project the lithofacies-sensitive elastic parameter volumes into the lithofacies classification probability distribution crossplot. Finally, we predict the spatial probability distribution of different lithofacies. Probabilistic characterization can enhance the recognition of transitional lithology and thin layers in the inversion results, reduce the uncertainty in the prediction of reservoirs and interlayers, and significantly improve the prediction accuracy of reservoirs and interlayers. The field application results in the Kinosis study area indicate that the probability volume predicted by this technology can distinguish interlayers greater than 1 m thick and identify interlayers greater than 2 m thick, which meets the technical requirements of oil-sand steam-assisted gravity drainage development.

Thermosensitivity experiments and simulation calculations were conducted on typical oil sand core samples from Kinosis, Canada to predict the steam chamber development with time-lapse seismic data during the steam-assisted gravity drainage (SAGD). Using an ultrasonic base made of polyether ether ketone resin instead of titanium alloy can improve the signal energy and signal-to-noise ratio and get clear first arrival; with the rise of temperature, heavy oil changes from glass state (at –34.4 °C), to quasi-solid state, and to liquid state (at 49.0 °C) gradually; the quasi-solid heavy oil has significant frequency dispersion. For the sand sample with high oil saturation, its elastic property depends mainly on the nature of the heavy oil, while for the sand sample with low oil saturation, the elastic property depends on the stiffness of the rock matrix. The elastic property of the oil sand is sensitive to temperature noticeably, when the temperature increases from 10 °C to 175 °C, the oil sand samples decrease in compressional and shear wave velocities significantly. Based on the experimental data, the quantitative relationship between the compressional wave impedance of the oil sand and temperature was worked out, and the temperature variation of the steam chamber in the study area was predicted by time-lapse seismic inversion.

海上稀井网油田的储层研究受制于缺少岩心,动态资料不完善等因素,精细表征储层分布规律的难度较大,井间预测具有很大不确定性.本次研究将珠江口盆地西江X油田珠江组海相砂岩储集层作为研究对象,以高质量地震资料和测井资料做基础,借助地震驱动确定性建模手段,探索出一套少井条件下海相辫状三角洲储层预测及建模方法,该方法突破了无井区域建模只能采用数学插值的传统做法,充分利用地震信息帮助,大幅提高了地质模型的准确性.

前期研究认为西江24-1油田珠江组下部H13-H10砂组是三角洲前缘或滨岸砂-陆架砂沉积,与新钻井揭示的砂体叠加样式、分布方向和厚度趋势相矛盾,砂体成因类型需进一步深入研究和探讨.本文通过古地理背景 、岩芯观察、沉积序列和相组合特征分析,结合测井相/地震属性与砂体分布特征,综合确定西江24-1油田珠江组中下段H13-H10砂组以潮控陆架沉积为主,发育潮道、潮砂坝、潮砂坪、浅海泥岩等微相.新认识合理解决了层段内砂体分布模式与新钻井之间的矛盾,对剩余油挖潜具有重要的指导意义.