Sheng, Xiaofei (Tianjin University) | Shen, Jianguo (Tianjin University) | Shen, Yongjin (Beijing Huahui Shengshi Energy Technology) | Zhu, Liufang (Logging Company of Shengli Petroleum Engineering Co.) | Zang, Defu (Logging Company of Shengli Petroleum Engineering Co.)
Transient electromagnetic (TEM) logging is a promising noncontact method for through-casing formation conductivity measurements. We studied the through-casing TEM logging method based on the processing of TEM logging data measured in a production well. Similar to Doll’s work in borehole induction logging, we presented the expressions of the ‘useful signal’ and the ‘useless signal’ in casedhole logging based on which, the methods of removing the ‘useless signal’ and obtaining the formation conductivity curve are introduced. We analyzed the influence of the casing on the TEM signals, described the characteristics of TEM response signals, and obtained the ‘useful signal’ carrying formation conductivity data. Casedhole formation conductivity curves, which are subsequently compared with the known openhole conductivity log, are obtained by dealing with the ‘useful signal’. We identified the characteristics of casedhole formation conductivity curves, and some problems that need to be considered in their practical application. Due to the influence of the casing, the radial detection depth of the TEM logging tool in a cased hole is small, so the detection result is mainly the equivalent conductivity of the cement ring and formation near the outer casing wall. Although the casedhole conductivity curves are in good agreement with openhole logging results in regular formations, due to the influence of the casing and the changes in the physical environment in the well, complete consistency is unrealistic for these two kinds of curves in all well intervals. Therefore, a thorough analysis is required before practical application. Moreover, the effects of well temperature and casing deformation must be corrected for accordingly.
It is well known that geophysics, particularly the
This course will present the workflows that have been developed along with spreadsheet-based exercises to solidify concepts. The workshop provides in-depth presentations and discussions of the models presented. This course examines datasets from both conventional and unconventional systems and present workflows to construct naturally-fractured reservoir models. Particular attention will be given to the use and calibration of a variety of 3D seismic attributes, which are critical to our characterization efforts. The combination of 3D seismic data with sound stratigraphic and structural frameworks provides a more robust fractured reservoir model.
There are several specific differences between exploration geophysics and reservoir geophysics, as the term is usually intended. The reservoir geophysicist should be familiar with the usefulness and limitations of petrophysical and reservoir-engineering studies and should be able to ask intelligent questions of the experts in those fields. However, the reservoir geophysicist typically is not an expert in those areas and works with the appropriate specialists to interpret the data or to design a new experiment to solve reservoir problems. In exploration, extrapolation of well data from far outside the area of interest is often necessary, and the interpretation is required to cross faults, sequence boundaries, pressure compartments, and other discontinuities that may or may not be recognized. The interpreter resorts to analogs in the absence of hard data, and local calibration of the geophysical response is generally poor.
Reliable estimation of geomechanical properties (i.e., Young's modulus and Poisson's ratio) of shale can provide important constraints to guide production by identifying sweet spots and locations for effective hydraulic fracturing. Amplitude Variation with Offset (AVO) inversion may make important contributions to such tasks, since it is an effective method to estimate elastic parameters of target layers. However, to estimate geomechanical and even elastic properties of shale from AVO inversion is not a trivial task, since organic-rich shale formations are often anisotropic. Our objective is to apply a nonlinear AVO inversion using the exact Zoeppritz solutions instead of its linear approximation. It allows estimation of seismic anisotropy and furthermore estimates of anisotropy of geomechanical properties. We first reformulate the exact Zoeppritz equations for reflection coefficients in terms of four parameters (one ratio of background P-wave and S-wave velocities, and three contrasts of P-wave and S-wave velocities, and density). An adjoint state technique is applied to compute the gradient of reflection amplitudes modeled by the parameters. This allows the nonlinear AVO inversion possible. We then propose a workflow to estimate seismic anisotropy and geomechanical properties of organic-rich shale. It is based on analyses of results from the AVO inversion. The anisotropy of the model shale is related to the kerogen volume fraction values using measured well logs and laboratory data for various shale formations. By applying inversion tests, we determine behaviors of the AVO inversion solutions developed for isotropic media when the target shale formation instead has seismic anisotropy related to organic content. These tests show that the inversion accurately determines horizontal P-wave and S-wave velocities and underestimates density when a far angle range is applied with input data. When the angle range is small, the inversion can obtain reliable vertical velocities, and correct density. Therefore, seismic anisotropy of the model can be estimated by comparing these inverted horizontal and vertical velocities. In addition, geomechanical properties of the model are also reliably determined in both horizontal and vertical directions. In contrast to most conventional AVO inversions based on linear approximations of the Zoeppritz equations, the proposed Zoeppritz AVO inversion is not limited by assumptions of weak contrasts and seismic isotropy. This allows better estimations of elastic and geomechanical properties and their anisotropy for unconventional shale play which are highly anisotropic and often surrounded by hard layers to generate strong contrasts. Given reliable inference of geomechanical properties from the AVO inversion, the results can directly impact to quantify fracability of unconventional play. Consequently, the workflow for nonlinear AVO inversion contributes to optimization of well placement, stimulated reservoir volume (SRV), and completion design of unconventional reservoir development.
Geophysics is a broad subject that encompasses potential field theory (gravity and electromagnetic fields) and seismic technology. Potential field data are valuable in many studies, but seismic data are used in more reservoir characterization and reservoir management applications. Seismic data have been used for many years to guide exploration. More recently, seismic data have been used to support reservoir characterization in field development planning and subsequent reservoir management. As the technology in equipment and interpretation techniques has advanced, so has the ability to define the size, shape, fluid content, and variation of some petrophysical properties of reservoirs.
Seismic data processing in deep-water slope belt area has always been a challenge for marine seismic data processing. Steep slopes could induce strong diffraction multiples, difficult velocity modelling, weaker illumination. This paper will introduce three key methods on dual direction acquisition seismic data imaging for slope belt area. The first key method is joint multiple attenuation, this method uses 3D SRME,vertex drift high-precision radon multiple attenuation, super CDP gather median filter to multiple attenuation; The second key method is geological constrained velocity modeling. This method uses geological information to restrict the initial velocity which could reduce the impact of rapid land surface change on velocity modeling; The third method is dual direction data merge. After PSDM, this method uses fast and slow wave velocity correction and advantage data to get a dual direction merging data stack section. Joint multiple attenuation could eliminate diffraction multiples effectively, and it can improve the signal to noise ratio which will be benefit for the velocity analysis and final imaging; Constrained velocity modeling could improve the velocity model accuracy in the steep slope area, which can help final imaging to avoid imaging distortion under steep seabed; To get a dual direction merging data stack section is a relabel way to increase data folds and illumination and improve the quality of imaging faults. The successful application of these three methods shows that dual direction acquisition data processing provides an effective way to solve the imaging difficulties in steep slopes in deep water.