Prime technologies

The best part of Prime is its unique technologies and algorithms. You can find a list of them below:

Ray-Born Modeling

3D Ray-Born Modeling is a technology used to generate high resolution acoustic and/or elastic synthetic seismic data based on a depth model defined by cubes of elastic parameters.

The depth model can be anisotropic with TTI anisotropy parameters and can also include Q absorption parameters. The very efficient target-oriented modelling allows to produce P and S synthetics up to 120 Hz. The results of this modeling technique can be instrumental in validating migration and inversion approaches, such as diffraction imaging, velocity model building, AVO analysis and Q estimation.

Boundary Integral Modeling

Boundary Integral Modeling (BIM) is a technology used to calculate synthetic seismic data. The algorithm is based on the finite element method combining Kirchhoff-type wave field transfer operators and optimal kinematic filtering operators. The method is for layered or blocky models especially when the model includes irregular interfaces combined with significant velocity contrasts. The method allows for the generation of P/S-polarized waves while considering the orientation characteristics of receivers within specified acquisition geometries.

The results of this modeling serve several purposes:

Testing structural hypotheses in depth model construction,

Validating kinematic and amplitude inversions,

Analyzing and compensating for amplitude distortions.

Ray-Born Demigration

Ray-Born Demigration is a technology used to calculate synthetic pre-stack and post-stack seismic data. The data obtained is characterized by kinematic and dynamic parameters derived from a depth model used in migration and the amplitudes in the image cube.

The modelling algorithm is based on a combination of the Kirchhoff integral approach applied to the top of each layer and wavefield redatuming to the top of the layer from each grid point within the layer.

The technology allows for efficient generation of seismic responses with a specified acquisition geometry and from local target structures in the subsurface.

The results of Ray-Born Demigration provide an effective model of reflected waves and are actively utilized in various stages of signal processing (statics, internal multiples, DI, etc.), as well as for correcting the amplitudes of seismic migration due to approximations in used seismic migration algorithms and possible migration artifacts due to given acquisition geometry.

Diffraction imaging (DI)

‘Diffraction Imaging’ (DI) is a seismic data processing technique that focuses on extraction of weak events hidden below strong reflections. The extracted events can include both diffractions as well as weak reflections with local dip different from the dip of the masking reflections.

Diffracted waves, which are deflected or scattered due to subsurface obstacles or discontinuities, often get overlooked in traditional seismic imaging.

However, these waves carry valuable information about small-scale subsurface features that reflection data cannot resolve. DI enables the identification of features like fractures, faults, karsts, and more.

Identifying such events provides interpreters with additional information, aiding assumptions about not only potential drilling danger zones but also reservoir structures.

We offer three DI technologies: Fresnel Zone-Based Migration (FZ-migration), Directional Gather Migration (DG-migration) and Generalized Fresnel Zone – Based Migration (GFZ).

1. FZ-migration separates the ‘reflected’ and ‘diffracted’ parts of the image based on the Fresnel zone for reflected waves. The migration aperture is split into two weighted parts, one for reflections and the rest for diffractions, calculated from the normal to the local dip at the image point. FZ migration results in conventional offset common image gathers, thus allowing conventional pre-stack post-migration processing.

2. DG-migration separates the reflected and diffracted parts of the image based on the angle between the normal to local dip and the bisector of source-receiver vectors at the image point. The advantage of DG is that separation happens after migration thus adding flexibility in the level of reflection-diffraction separation.

3. GFZ -migration combines the best of the two approaches. It results in CIGs as a function of both offset and the difference in Green’s function travel time for reflections and diffractions within Kirchhoff migration. It allows both post-migration reflection-diffraction separation and conventional post-migration pre-stack processing.

• All three techniques can be enhanced by pre-suppressing the "mirror" component through modeling (de-migration) and adaptive subtraction.

Depth model-driven seismic data processing

Time processing, utilizing a model of average velocities, is a standard practice in seismic exploration. This method uses time migration to generate images of the medium.

However, this approach may be ineffective for the problems of complex structural formations and amplitudes. In such scenarios, depth processing, which uses models closer to the actual medium, may be a better alternative. This technique retains the kinematic parameters and amplitudes of the signals, producing a more accurate depth image of the medium.

To fully benefit from depth migration, the entire processing workflow should be conducted in a corresponding depth model, not an average velocity model. Furthermore, data prepared for time processing may not be compatible with depth migration. The technology we employ is based on a depth model from the early stages of processing. This allows complex and resource-intensive procedures, like modeling, to be performed in the most natural way while optimally utilizing computational resources.

Kirchhoff Migration

The Kirchhoff migration program is used to obtain depth images. This program performs in true amplitudes. Its unique feature is its focus on a generalized layered model of the medium, which is constructed during the stage of solving the inverse kinematic problem.

This means that the algorithm takes into account various factors included in the model, such as contrast boundaries, anisotropy, and the gradient for the specified layers. It allows the layers to be described as a set of conformal layers with laterally varying parameters.

A special migration mode is used to construct seismic sections at varying incident/reflection angles. In this mode, the program determines the dependence of the incident/reflection angles on the distance on the seismic sections from the common image point. This information is then used to obtain angle gathers.

Migration can be performed from different datums of source and receiver location. This is particularly relevant when processing OBC/OBN data. The program also allows for the possibility of multiple wave migration.

The program includes data interpolation capabilities in the area of "constructive summation". This partially compensates for the shortcomings of the observation system and can be optionally implemented.

The program is well-optimized for parallel processing on distributed computing resources, making it suitable for handling large volumes of data.

Velocity model building

Today depth migration is the main tool for obtaining of seismic images of the media. Correct accounting and compensation for a velocity anomalies and seismic anisotropy requires velocity models of high quality. Our company uses Prime technology of velocity model building. It uses nonlinear algorithms to solve the inverse problem and do not require initial model building. Also, as the advantage, it utilizes interpretative approach from very first steps of model building. This allows to obtain high-quality geologically reasonable velocity models consistent with all priori data.

Our company’s specialists have many years of practical experience in velocity model building for geological media of high complexity. The tools and technologies we use to solve this problem allow us successfully operate both in conditions of complex tectonics and in the presence of various anomaly objects, such as salt or magmatic intrusive bodies of complex shape.

Q-migration

Conventional Kirchhoff migration fails to accurately restore the amplitudes and spectrum of reflections in areas with high absorption anomalies (low Q values). A correct structural interpretation and accurate AVA analysis cannot be achieved without compensating for distortions caused by seismic absorption.

To address this, we propose two technologies to accurately compensate for the influence of seismic absorption, considering the propagation trajectories of reflected waves:

1. Attribute Q-migration. This technology performs two prestack depth migrations. The first is conventional, and the second uses a special marker function that encodes the Qeff values along the ray paths forming the image. After this migration, Qeff information can be extracted at each point in the resulting image and inverse Q filtering applied. However, the inverse Q-filtering can introduce a large amount of noise at high frequencies and cannot be controlled during migration. Thus, the advantage of this approach is the absence of inverse Q-filtering in the depth migration engine, moving it to the post-migration stage.

2. Inverse Q-filtering based on reference Q-demigration. In this method, the stage of weakly controlled inverse Q-filtering during migration is replaced by forward Q-filtering applied during the calculation of synthetic data by Q-demigration of the stacked seismic cube. Subsequent migration of such synthetic seismic data allows the construction of matching filters that compensate for calculated absorption effects. These filters are applied to the result of the migration of the original seismic data.

Signal Processing

In signal processing, a broad array of algorithms for noise suppression and signature correction is utilized.

Additionally, various procedures and techniques are employed to address specific seismic data processing issues. These include programs for modelling and subtraction different types of noise, primarily surface and internal multiples.

Our multi-channel and multi-dimensional adaptive subtraction includes different types of robustness minimizing the level of residual noise and effects of distortion of primaries, and it accounts for (smooth) non-stationarity of the required adaptive subtraction filters.

Non-stationary deconvolution programs, programs for estimating parameters and correcting frequency-dependent absorption, as well as programs for robust (sparse) deconvolution and phase spectrum correction of signals are also utilized.

Multiples modeling and subtraction

The software system offers various methods for modelling, prediction and adaptive subtraction of multiples:

• Modelling and prediction of free-surface multiples

• Modelling and prediction of water-layer multiples and peg-legs

• Modeling and prediction of internal multiples

• Both modelling of multiples and prediction of multiples are performed using wavefield re-datuming with boundary-integral approach.

The module for multi-dimensional and multi-channel adaptive subtraction allows simultaneous adaptive subtraction of several multiple terms. It includes special features like ‘robustness’ allowing improved preservation of primaries and non-stationarity of the adaptive subtraction filters minimizing the level of the multiple residuals.