Simultaneous joint migration inversion for high-resolution imaging/inversion of time-lapse seismic datasets

The current time-lapse practice is to exactly repeat well-sampled acquisition geometries to mitigate acquisition effects on the time-lapse differences. In order to relax the rigid requirements on acquisition effects, we propose simultaneous joint migration inversion as an effective time-lapse tool for reservoir monitoring, which combines a joint time-lapse data processing strategy with the joint migration inversion method. Joint migration inversion is a full-wavefield inversion method that explains the measured reflection data using a parameterization in terms of reflectivity and propagation velocity. Both the inversion process inside the imaging/inversion scheme and the extra illumination provided by including multiples in joint migration inversion makes the obtained velocity and reflectivity operator largely independent of the utilized acquisition geometry and, thereby, relaxes the strong requirement of non-repeatability during the monitoring. Because simultaneous joint migration inversion inverts for all datasets simultaneously and utilizes various constraints on the estimated reflectivities and velocity, the obtained time-lapse differences have much higher accuracy compared to inverting each dataset separately. It allows the baseline and monitor parameters to communicate with each other dynamically during inversion via a user-defined spatial weighting operator. In order to get more localized time-lapse velocity differences, we further extend the regular simultaneous joint migration inversion to a robust high-resolution simultaneous joint migration inversion process using the time-lapse reflectivity difference as an extra constraint for the velocity estimation during inversion. This constraint makes a link between the reflectivity- and the velocity difference by exploiting the relationship between them. We demonstrate the feasibility of the proposed method with a highly realistic synthetic model based on the Grane field offshore Norway and a time-lapse field dataset from the Troll Field.     

云南地区GNSS应变场时空演化与地震事件关联分析

采用GAMIT/GLOBK软件对云南境内及邻区近400个GNSS测点1999～2018年的观测数据进行解算,在各个测点时间序列和速度场的基础上,采用克里金插值方法分时段估计该区域在1999～2004年、2004～2007年、2009～2013年、2013～2015年、2015～2018年共计5个时间区域应变率场;根据区域地壳面应变率和最大剪应变率的空间变化以及相应时段之后3年内的MS≥5. 0地震事件分布特征,分析发现:绝大部分震例发生在面应变高梯度带的张压转换区和最大剪应变高值区,可见研究区各个观测时段GNSS应变率场对后期1～3年内的中强震发生区域有一定的指示意义;以2014年盈江6. 1级、鲁甸6. 5级和景谷6. 6级地震为样本,建立监视块体获取应变时间序列,分析发现:地震前三个月左右均出现震中附近短期应变趋势改变、快速增强、转折的现象,这些形变异常变化或许反映了发震区应力-应变积累在接近临界破裂状态时的非线性调整,为地震短临预测尤其是时间要素的判断提供参考。     

基于GPS连续运行基准站的中国区域共模误差研究

共模误差是GPS台站位置时间序列中的主要误差源之一,分离和消除共模误差可以探测到原先淹没在噪音中的微弱信号。本文对中国260个卫星导航定位基准站2011～2018年的数据进行处理,获得了位置时间序列,采用主成分分析（PCA）方法对其扣除构造运动等形变信号后的残差序列进行区域共模误差分析。结果表明,PCA方法有效地提取了中国区域共模误差,经过滤波后时间序列的信噪比明显提高,第一主分量空间分布均一,第二主分量空间分布呈现明显的梯度变化,表明第二主分量不是少数台站的局部效应,是对第一主分量的补充和修正,中国区域的共模误差分析不能忽略二阶分量。对振幅调制的影响进行了对比分析,发现顾及振幅调制的共模误差不仅明显减弱了年周期的特征,还显著降低了闪烁噪声,表明由于参数过于简化而未被估计的“信号”会演变成共模误差,未被正确模型化的“信号”会影响区域滤波的准确性。     

环境负载对云南地区基准站时间序列的噪声模型特性研究

以云南地区27个GPS基准站坐标时间序列为研究对象,使用赤池信息量和贝叶斯信息量估计准则（AIC/BIC）对其进行噪声分析,计算并扣除时间序列中大气负载、非潮汐海洋负载和水文负载3种环境负载引起的位移量,得到各基准站分量在环境负载改正前后的最优噪声模型。结果表明,部分基准站分量经过负载改正后最优噪声模型会发生变化,改正前后的大部分基准站噪声特性均体现为闪烁+白噪声和幂律噪声。环境负载对基准站的垂向位移影响比水平向更为显著,水文负载成为影响基准站的最大因素,最大位移量达到厘米级。分析环境负载改正前后噪声特性的变化表明,环境负载改正在U分量上的影响最大,N分量次之,E分量最小,噪声模型的变化在地域上并未呈现明显规律。     

多时间尺度下SS-Y伸缩仪对气压效应的响应分析

整理淮北台2014年以来SS-Y伸缩仪观测资料,分析其在年、月、日和短时(数十分钟)不同时间尺度下对气压效应响应的差异,通过建立适当的数学模型拟合出相应的响应曲线,结果表明:在短周期时间尺度下SS-Y伸缩仪对气压效应的修正方程改进效果显著。     

Marine transient electromagnetic sounding of deep buried hydrocarbon reservoirs: principles,methodologies and limitations

The possibility of a time‐domain electromagnetic sounding method using excitation and measurement of vertical electric fields to search for and identify deeply buried reservoirs of hydrocarbons offshore is investigated. The method operates on source–receiver offsets, which are several times less than the depth of the reservoir. Geoelectric information is obtained from the transient responses recorded in the pauses between the pulses of electric current in the absence of the source field. The basics of the method, as well as its sensitivity, resolution, and the highest accessible depth of soundings for various geological conditions in a wide range of sea depths, are analyzed. For the analysis, 1D and 3D geoelectric models of hydrocarbon reservoirs are used. It is shown that under existing technologies of excitation and measurement of vertical electric fields, the highest accessible depth of soundings can be up to 4 km. Technology for the inversion and interpretation of transient responses is demonstrated on experimental data.     

Time-frequency analysis based on curvelet transforms with time skewing

Oil and gas exploration gradually changes to the deep and complex areas. The quality of seismic data restricts the effective application of conventional time-frequency analysis technology, especially in the case of low signal-to-noise ratio. To address this problem, we propose a curvelet-based time-frequency analysis method, which is suitable for seismic data, and takes into account the lateral variation of seismic data. We first construct a kind of curvelet adapted to seismic data. By adjusting the rotation mode of the curvelet in the form of time skewing, the scale parameter can be directly related to the frequency of the seismic data. Therefore, the curvelet coefficients at different scales can reflect the time-frequency information of the seismic data. Then, the curvelet coefficients, which represent the dominant azimuthal pattern, are converted to the time-frequency domain. Since the curvelet transform is a kind of sparse representation for the signal, the screening process of the dominant coefficient masks most of the random noise, which enables the method to adapt for the low signal-to-noise ratio data. Results of synthetic and field data experiments using the proposed method demonstrate that it is a good approach to identify weak signals from strong noise in the time-frequency domain.     

Probabilistic downtime estimation for sequential marine operations

A marine project consists of series of operations, with each operation subject to a predefined operational limit and duration. If actual weather conditions exceed the operational limit, the operation cannot be executed and hence downtime occurs. An accurate assessment of uncertainties and the expected downtime during a marine project is important in the tender and execution phase. This paper proposes a new probabilistic model for downtime estimation. It utilizes linked Markov chains that use actual metocean conditions to produce binary workability sequences for each operation. Synthetic time-series can be generated based on the statistics of the past observations and more project simulations are realizable, reducing the simulation uncertainty. The capabilities and limitations of the proposed approach are illustrated in a case study for a hypothetical project in the Tasman Sea.     

Characterizing spring phenology of temperate broadleaf forests using Landsat and Sentinel-2 time series

Vegetation phenology has a great impact on land-atmosphere interactions like carbon cycling, albedo, and water and energy exchanges. To understand and predict these critical land-atmosphere feedbacks, it is crucial to measure and quantify phenological responses to climate variability, and ultimately climate change. Coarse-resolution sensors such as MODIS and AVHRR have been useful to study vegetation phenology from regional to global scales. These sensors are, however, not capable of discerning phenological variation at moderate spatial scales. By offering increased observation density and higher spatial resolution, the combination of Landsat and Sentinel-2 time series might provide the opportunity to overcome this limitation.In this study, we analyzed the potential of combined Sentinel-2 and Landsat time series for estimating start of season (SOS) of broadleaf forests across Germany for the year 2018. We tested two common statistical modeling approaches (logistic and generalized additive models using thin plate splines) and the two most commonly used vegetation indices, the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI).We found strong agreement between SOS estimates from logistic and spline models (r_EVI = 0.86; r_NDVI = 0.65), whereas agreement was higher for EVI than for NDVI (RMSD_EVI = 3.07, RMSD_NDVI = 5.26 days). The choice of vegetation index thus had a higher impact on the results than the fitting method. The EVI-based SOS also showed higher correlation with ground observations compared to NDVI (r_EVI = 0.51, r_NDVI = 0.42). Data density played an important role in estimating land surface phenology. Models combining Sentinel-2A/B, with an average cloud-free observation frequency of 12 days, were largely consistent with the combined Landsat and Sentinel-2 models, suggesting that Sentinel-2A/B may be sufficient to capture SOS for most areas in Germany in 2018. However, in non-overlapping swath areas and mountain areas, observation frequency was significantly lower, underlining the need to combine Landsat and Sentinel-2 for consistent SOS estimates over large areas. Our study demonstrates that estimating SOS of temperate broadleaf forests at medium spatial resolution has become feasible with combined Landsat and Sentinel-2 time series.     

质量控制在HLJCORS建设中的实现

从黑龙江省地域特点、质量控制的内容及质量控制的方式方法 3个方面,介绍了HLJCORS建设的质量管理和控制,总结出HLJCORS建设质量控制经验。