Detecting small subsurface features such as faults, fracture swarms, steep reef edges, and channel edges is a routine task in seismic interpretation. Common seismic attributes used for this task, such as curvature and incoherence, are derived from conventional images containing both reflections and diffractions. An emerging alternative approach is to interpret these edge features using the diffraction-imaging technique, which images diffracted energy separately. A diffraction-imaging volume is generated by separating specular reflections from diffractions in an unmigrated volume followed by migration of those diffractions. Different methods can be used to separate diffractions from reflections on unmigrated data. In a case history, they are separated with a plane-wave destruction (PWD) filter. An evaluation of diffraction-imaging performance is applied to a 3D seismic data set from the Cooper Basin of Australia. Diffraction-imaging horizon maps are compared with corresponding maps made from incoherence and curvature volumes. The resolution and the ability to detect faults, fractures, and channel-edge features are compared. The results show that diffraction imaging provides superior vertical and spatial resolution over conventional incoherence and curvature attributes for mapping faults and stratigraphy.
It is generally believed that the incomplete return of treating fluids (flowback) is a reason for the failure of hydraulic fracturing and it is associated with poor gas production. Capillary effects and fracture face skin are known to be the main parameters that limit flowback in tight gas sands. However, near-wellbore pressure loss during the main operation of hydraulic fracturing and its effects on flowback are not well understood. In the case of pre-existing natural fractures in a reservoir, near-wellbore pressure loss is high mainly because multiple fractures with tortuous paths are often created. Also, it is believed that this tortuous path causes shear dilation in natural fractures and opens the closed fractures. As a result, there is a large amount of pressure dependent leakoff. Therefore, pressure dependent leakoff has both positive and negative impacts. It can increase rock permeability and at the same time it can cause a high near-wellbore pressure drop. Hence, near-wellbore pressure needs to be reduced in order to have better proppant placement and maximize the fracturing fluid flowback. For this research, several hydraulic fracturing treatments in the Patchawarra formation in the Cooper Basin, South Australia have been studied. There are some pre-existing natural fractures in our case study. The bottom-hole treating pressure has been analysed with 600 psi of near-wellbore pressure loss causing a low percentage of proppant placement. We constructed a 3D hydraulic fracturing model coupled with multiphase flow simulation for the prediction of flowback of water and gas production. Several injection fall-off tests were first interpreted and found that the leakoff is pressure dependent. Our simulation has shown that high near-wellbore pressure loss has an impact on the effectiveness of the fracture treatment. This results in a shorter fracture length and low pressure distribution inside the fracture that leads to a low recovery of fracturing fluid. As a result, we have successfully provided recommendations for best practice to reduce near-wellbore pressure loss.
We have developed a tight gas amplitude variation with offset (AVO) case history from the Cooper Basin of Australia that addressed the exploration problem of mapping thin fluvial tight gas sand bodies. In the Cooper Basin, Permian Toolachee and Patchawarra sands are difficult to interpret on seismic data due to strong reflections from adjacent Permian coals. This is not the common AVO problem of distinguishing between coal and gas sand, but a more difficult class-I AVO problem of mapping fluvial sands beneath a sheet coal that varies in thickness. We have reviewed local rock properties and concluded that Poisson's ratio is probably the most appropriate rock property to solve the above exploration problem. We have compared various seismic attributes made using the extended elastic impedance (EEI) technique and a rotation of near and far partial stacks. In a synthetic modeling study that included random noise and tuning, we compared the noise-discrimination abilities of three competing AVO crossplot techniques and "rotated" the attributes made from them. These three crossplots were as follows: intercept versus gradient (I-G), full-stack versus far-minus-near (Full-FmN), and near-stack versus far-stack (N-F). Previous papers on this subject have found that (I-G) crossplots had a spurious correlation in the presence of noise that did not occur with the (Full-FmN) and (N-F) crossplots. We found that for our class-I AVO case, (1) the advantage of the (Full-FmN) and (N-F) crossplots disappeared in the presence of tuning, (2) if tuning was present, the optimal rotation angle was determined by the "tuning angle," not by the noise angle or some desired EEI angle, and (3) if the three different crossplots were rotated by their respective "tuning" angles, the results were identical.
Theoretically, vertical fractures and stress can create horizontal transverse isotropy (HTI) anisotropy on 3D seismic data. Determining if seismic HTI anisotropy is caused by stress or fractures can be important for mapping and understanding reservoir quality, especially in unconventional reservoirs. Our study area was the Cooper Basin of Australia. The Cooper Basin is Australia’s largest onshore oil and gas producing basin that consists of shale gas, basin-centered tight gas, and deep coal play. The Cooper Basin has unusually high tectonic stress, with most reservoirs in a strike-slip stress regime, but the deepest reservoirs are interpreted to be currently in a reverse-fault stress regime. The seismic data from the Cooper Basin exhibit HTI anisotropy. Our main objective was to determine if the HTI anisotropy was stress induced or fracture induced. We have compared migration velocity anisotropy and amplitude variation with offset anisotropy extracted from a high-quality 3D survey with a “ground truth” of dipole sonic logs, borehole breakout, and fractures interpreted from image logs. We came to the conclusion that the HTI seismic anisotropy in our study area is likely stress induced.
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