Imaging the geology subsalt and at the transition between extra-salt and subsalt has been a challenge at Mad Dog even with extensive seismic data coverage, including two WATS surveys and multiple NATS surveys. WATS acquisition and TTI velocity model processing generated major improvements in the image at Mad Dog. One of the observations of a previous TTI project is the presence of a strong orthorhombic anisotropic effect in a salt mini basin above the field. This finding led to the decision to reprocess the Mad Dog data with a tilted orthorhombic (TOR) velocity model. The main objective of this project is to build an orthorhombic velocity model with nine parameters compared to five with the TTI processing. The TOR anisotropic parameters are generated with the latest FWI and tomography techniques and take guidance from the stress field from a geomechanical model. The outcome of the project is very encouraging with results including better constructive imaging in crucial areas of the field, an incremental increase in signal-to-ratio everywhere and increased fault resolution. The TOR velocity model will be used to migrate a future ocean bottom nodes survey to address some of the remaining imaging challenges.
Presentation Date: Wednesday, October 17, 2018
Start Time: 8:30:00 AM
Location: 208A (Anaheim Convention Center)
Presentation Type: Oral
Li, Qingsong (BP) | Reitz, Anya (BP) | Jia, Tianxia (BP) | Hartman, Kenneth (BP) | Rollins, Francis (BP) | Slopey, William (BP) | Deren, Gary (BP) | Michell, Scott (BP) | Naranjo, John (BP) | Abma, Raymond (BP) | Mahnke, Michael (Schlumberger)
In June and July, 2015, BP successfully acquired Thunder Horse and Mad Dog 3D VSPs in the Gulf of Mexico (GoM). The objective was to get high resolution subsalt images in the reservoirs beneath the wellbore receiver arrays, where subsalt illumination is poor and surface seismic images are inadequate to fulfill business needs. Compared with previous BP’s 3D VSPs, the two recent surveys used a longer receiver tool (2km, 100 levels), denser source grids (75mx87m and 75mx50m), and targeted source patch. The wireline recording and source vessels operated nearly independently and were integrated with GPS timing to reduce technical complexity. The surveys were acquired safely and efficiently (3.2 days production shooting for Thunder Horse with 2 source vessels and 7.4 days production shooting for Mad Dog with 1 source vessel). The recorded data in both surveys are good quality with only a small percentage of failed and noisy channels. The two surveys broke the world record of 3D VSPs in terms of number of recorded traces. The 3D VSP data were processed and migrated, producing high quality seismic images that generated significant business value. In this paper, we present our experiences and learnings during modelling, planning, acquisition design and operation of these two 3D VSPs.
Presentation Date: Thursday, October 20, 2016
Start Time: 8:55:00 AM
Presentation Type: ORAL
Summary 3D VSP data provides a unique opportunity to improve image resolution and fault definition in the vicinity of a well. However, the processing and imaging of VSP data requires special accommodations for its distinctive acquisition geometry. In this abstract, we demonstrate two key VSP pre-processing steps that greatly impacted the final image from the Mad Dog 3D VSP data, including XYZ vector field reorientation based on 3D elastic finitedifference modelling, and shot-to-shot directional designature using near field hydrophone data. We also discuss how utilizing the multiple energy - in addition to primary - extends our capability to image the shallow overburden. However, small gyroscopes often drift from their original positions, and inclinometers may increase the cost and weight of downhole receivers (Greenhalgh et al., 1995).
Accurately predicting the effective image area of a 3D VSP can be a difficult task to accomplish. The creation of a field wide Finite difference earth model at the Mad Dog Field provided the opportunity to perform forward modeling of an already existing 3D VSP in order to calibrate expectations of image area on possible future VSP acquisition. The acquired 3D VSP, which had recently been reprocessed, was modeled by conducting acoustic wave equation forward modelling and migrated with reverse time pre-stack depth migrations (RTM) and wave equation migrations (WEM) of the synthetic data. These data were then stacked and compared to the images from the acquired VSP.
At first look, the finite difference model VSP image area was much larger than the image area of the acquired VSP. One problem was that the RTM produced a much more extensive image both above and below the receivers, a function of the algorithm being able to handle both upgoing and down-going energy. The WEM, however, could handle only up-going energy, and produced an image closer in appearance to the VSP processed image. Although the acquired VSP was processed with a reverse time migration, the down-going energy contribution was much less robust than that of the modeled data; this could be due to the velocity model errors in the real world case. Differences between the acquired VSP and the modeled WEM may also be due to velocity model errors in the actual VSP processing. With both migration types, it became apparent that the modeled image areas would likely be interpreted as being significantly more extensive than the actual realized image. However, through detailed inspection, it was possible to determine which areas of the modeled image needed to be discounted. This ultimately resulted in a predicted image that was very similar to the actual VSP image. These learnings were subsequently applied to the modeling of a planned VSP acquisition in a different well, and impacted both the source pattern design and the expected image.
The Mad Dog Field is a giant subsalt field in the Gulf of Mexico, discovered by BP in 1998. The field started producing in 2005. The field lies beneath the edge of the Sigsbee Escarpment in 4000 to 7000 feet of water approximately 190 miles south of New Orleans
Summary Newly reprocessed seismic data reveals a bright shallow amplitude and underlying feeder pattern at the Frampton anticline, part of the Atwater Valley-Southern Green Canyon fold belt in the deep water Gulf of Mexico. Multiattribute geobody extraction produces a 3D view of this feature, which provides insight into the extents and possible history of the feature. Introduction The Frampton structure is a salt-cored anticline located outboard of the Sigsbee Escarpment in southern Green Canyon, Gulf of Mexico (Figure 1). A well was drilled on this structure in 2001 on an earlier vintage of seismic data (Figure 2a), and found a small biogenic gas accumulation in the Upper Miocene but no oil in the Middle and Lower Miocene target zones. Seismic line from 2001, around the time the well was drilled at Frampton.
A 3D wave-equation migration algorithm has been developed to image salt flanks with transmitted arrival VSP data. A precise knowledge of the salt flank location is often essential for accurate resource estimates and optimal well planning. The traditional salt-proximity survey provides a poorly constrained line in 3D space. In this abstract we develop a method to image the full salt surface by utilizing long-offset walk-away and 3D VSP datasets that are frequently acquired for imaging purposes. The method has been successfully demonstrated on a real data example.