Time Imaging

SIP offers the full range of 2D and 3D Time Processing services, from field tapes through to final migration. We have the breadth of experience to be able to tailor our processing to specific interpretation requirements e.g. AVO, Inversion etc. Our core processing software is ProMAX, which is the most widely used in the industry.

New processes:

• 3D Velocity Azimuth Frequency Filter
• Neural Net Dense Velocity Picking - Using 4th order
• ETA Scanning for PSTM
• Gather Conditioning for AVO
• Kirchhoff (Anisotropic Curved Ray)

Simultaneous Derivation of Velocity and Anisotropic Parameters

• Simultaneous 2D/3D Pre-stack Time Migration and velocity Field estimation
• SIP has exclusive rights to DMI AutoImager Technology in Europe!

SIP provides a unique technique which simultaneously derives an accurate velocity field for the pre-stack time migration, as well as the optimum migrated image. The migration is curved ray using the anisotropic parameter Eta, which is resolved along with the velocities.

It is an iterative approach, with minimal user input, which minimizes turnaround time significantly and avoids human error. It is a fundamental step up from conventional auto-picking approaches.

• Objectively determined velocities & true quality Image
• Decreased project turnaround time
• Designed to extract maximum information from time migration
• Consistency in amplitudes for reliable AVO & Elastic Inversion.
• High resolution velocity model suitable for input to 3D Tomography.
• Depth conversion is reliable due to a consistent velocity field.
• Repeatability of results.
• Anisotropic curved ray algorithm produces flat gathers & consistent Eta.

This simultaneous, data-driven approach is widely used at SIP for both land & marine data.

It is also a very important step before Simultaneous Inversion because of its correct amplitude handling, which is a key feature in risk reduction.

Conventional PSTM

SIP PSTM

Unlike conventional velocity analysis, out technology uses four main factors to derive velocities for migration. This allows you to build a more accurate model and extract the optimum image from your data.

The interval velocity model derived is clear and consistent with structure