Quantitative and Qualitative Seismic Interpretation of Seismic Data
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Quantitative and Qualitative Seismic Interpretation of Seismic Data

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Quantitative and Qualitative Seismic Interpretation of Seismic Data Quantitative and Qualitative Seismic Interpretation of Seismic Data Document Transcript

  • 1 Quantitative and Qualitative Seismic Interpretation of Seismic Data The primary aim of qualitative seismic interpretation is to map the subsurface geology. Qualitative interpretation is conventional or traditional seismic techniques that include the marking of laterally consistent reflectors and discontinuous characteristics like faults of various types and their mapping on different scales (space & travel time). The geometry on the seismic section is precisely interpreted in view of the geological concepts to detect the hydrocarbon accumulation. The Structural and stratigraphic architecture of the petroleum system is determined and on behalf of these geometric features the location of the well is established. As compared to the conventional qualitative seismic interpretation, the quantitative seismic techniques from the previous two decades proved itself more useful than the traditional technique or the art of interpretation. In which the physical variations of the amplitudes is considered to predict the hydrocarbon accumulation. Various alterations in these techniques have contributed to better prospect evaluation and reservoir characterization. Particularly, the unconventional techniques widen the exploration areas. They validate hydrocarbon anomalies and make prospect generation easier.
  • 2 Unconventional reservoirs: Unconventional reservoirs of hydrocarbons are those which have very less permeability and porosity. Usually their production is carried on by enhanced oil recovery techniques, such as fracture stimulation or steam injection, etc. Main types of unconventional gas reservoirs: Tight gas – Very refined techniques are required to reduce the migration distances from the formation to the well. This source of energy is rapidly emerging. Formation has low permeability. It needs the flow area to be deep into formation to get cost effective production. Stimulation and cementing technologies are promising for future economic production. Shale gas – These are organically loaded gas shale reservoirs. The hindrances met are while releasing gas from rock that is as solid as concrete. Gas hydrates – Seismic surveys point out the reserves to be in ample amount in offshore areas and under permafrost in few arctic areas. Recovery of this resource is challenging and there are e safety concerns regarding environmental in it. Conventional seismic interpretation techniques cannot easily identify these unconventional reservoirs. So, to resolve this difficulty we use various unconventional seismic interpretation techniques as discussed below.
  • 3 Unconventional Seismic Interpretation Techniques include following;     AVO Analysis Seismic Inversion Seismic Attributes Forward Seismic Modeling AVO Analysis Amplitude versus offset (AVO) is primarily the variation in seismic reflection amplitude with change in distance between shot point and the receiver. Its another name is AVA (amplitude variation with angle). AVO analysis is conducted on CMP data, where the offset rises with the angle. Increase in AVO on the seismic section are the identifications of softer reservoir rock with hydrocarbons (low acoustic impedance) than ambient shales and decrease in amplitude with offset is because of geometrical spreading, attenuation, absorption, anisotropy and several other aspects. Historical Background: The bright spot technique was applied as earlier as 1972 as commercial tool for the hydrocarbon prediction. In Gulf of Mexico it was quite successful where bright spot amplitude would coincide with gas filled sands. However, it wasn’t very much applicable in several other regions. Occasionally the volcanic intrusion or volcanic sill found with high impedance and some other lithologies with the high contrast of impedance compared with inter bedded shale. This failure is because of lack of consideration of wavelet phase. Also, it has been observed that gas filled sands lead to dim spot, when sands with high impedance compare to ambient shale bodies. After a few years, in 1984 Ostander presented the major failure of the bright spot technique in his research paper. He demonstrated that presence of gas in a sand strata capped by a shale would lead to higher amplitude variation with offset in pre-stack seismic data. Also he found that this change was secondary to reduction of Poisson’s ratio caused by gas. Later Zoepprits equation verified the Poisson ratio to be directly related with offset dependent reflectivity for up to 30˚ of incident angles. AVO technique was much more appreciated and it can explain physically the properties in terms of rock physics. It can physically explain presence of hydrocarbon in the reservoirs and the thickness, porosity, density, velocity, litho logy and fluid content of the reservoir of the rock can be estimated. Then bright spot techniques are suggested for use before stack data. Draw backs of AVO Analysis:   Lithology, tuning & overburden effects create ambiguities. The processing and aqusition effects may lead to false AVO anomalies.
  • 4    The common reason for failure being lack of shear wave velocities information and use of simple geologic models. Also, the professionals must be expert and experienced for geologic input. Processing techniques that affect the near offset traces (CDP Gathers) in different way from far offset traces could also lead to false AVO anomalies. The 3D acquisition supports the AVO technique. Reason being its disciplined surveying and improved pre-processing routines. It has more frequent shear wave logging and better perception of rock physics properties. In fact, the technique didn’t failed itself but the inappropriate use of it leads to difficulties and spurious outcome. Forward seismic modeling It is very useful tool for acquisition, processing and interpretation of seismic data. In Seismic modeling the geologic computer models are constructed followed by stimulation of seismic wave propagation response. In brief, it can be considered as numerical computation of theoretical seismograms for geological model of the subsurface. The forward modeling of geophysical data is applied as a tool for survey design aid and with the help of it the interpretation of recorded or processed seismic data is constrained. The synthetic seismic records can be used to assess whether an expected geologic target will generate an interpretable signature on output processed data or not. For the complicated structures, forward modeling of seismic data helps us to develop advanced techniques of imaging. It is used before and after the acquisition of seismic field data. The main points to be mentioned are:    Its application in all 1D, 2D and 3D data. It can be performed in frequency, time and frequency-wave number domain. It can be mapped for Cylindrical Coordinates, Cartesian Coordinates, and also the Spherical Coordinates. Methods: Convolution model: It is the convolution of the wavelet and the reflectivity. This model is quite simple yet useful. Though convolution model appears to lack some physics, however, it’s still useful. The seismogram we build by convolution model is migrated seismic profile and can be compared to the final seismic images.
  • 5
  • 6 These are two examples include geologic model and corresponding vertical incidence synthetic seismic section. Left one shows the seismic response of lateral variations in the thickness of individual sedimentary layers. This phenomenon is called “pulled up”. In right one, amplitude variations along a specific reflection can occur as the result of lateral changes in acoustic impedance contrast. Reflectivity method: For the generation of the complete elastic body-wave responses from a horizontally layered system; including all possible multiples, mode conversions, and transmission losses. Reflectivity modeling is still widely used due to its specific properties. All possible modes are calculated. This method can model almost all kinds of waves propagating in elastic or inelastic media with high numerical stability and accuracy but relatively less computation cost. Since the point source radiates both P and S (S) waves, we can see both reflected P waves (PP) and S waves (SS) corresponding to the incident P waves and S waves among the early arrivals. Thus, this method can calculate all possible modes. The left one is modeling data without multiples, just reflections and transformed waves. The right one is designed to show multiples within the same earth model.
  • 7 Seismic Inversion It is defined as process of converting seismic reflection data into a quantitative rock-properties of a reservoir. Seismic inversion may be pre-stack or post-stack, deterministic, random or geostatistical. It includes other reservoir measurements like well logs and cores. The process of moving rocks on the left to seismic on the right is labeled as “seismic method”. On the left we have rock property Acoustic Impedance (Reflectivity). Then moving left to right in below diagram changes in Reflectivity at horizon boundaries results in normal incident reflection coefficients. The reflection coefficient is replaced by a wavelet is centered and weighted by the reflection coefficient. These individual wavelets are summed and uncorrelated noise is added to generate the seismic trace. The process of seismic inversion takes us in the opposite direction trying to determine the Acoustic Impedance of the individual rock layers. Seismic data may be inspected and interpreted on its own without inversion, but this doesn’t provide most detailed view of the subsurface and can be misleading under certain circumstances. Because of its efficiency and quality, most oil and gas companies now use seismic inversion to increase the resolution and reliability of the data and to improve estimation of rock properties including porosity and net pay. All recent and advanced seismic inversion methods need seismic data and a wavelet estimated from data. A reflection coefficient series from a well within the boundaries of seismic survey is
  • 8 used to estimate the wavelet phase and frequency. Accurate wavelet estimation is very important for the success of any seismic inversion. The inferred shape of the seismic wavelet may strongly affect the seismic inversion results and also the assessments of the reservoir quality. Wavelet amplitude and phase spectra are estimated statistically from either the seismic data alone or from combination of seismic data and well control using wells with available sonic and density curves. The seismic wavelet is subsequently used to estimate seismic reflection coefficients in the seismic inversion. Benefits of Seismic Inversion The concept of impedance and geology is better understood by most geologists than the seismic trace. Thus working in the impedance domain is a great mechanism for coordinating with the various disciplines in a multidisciplinary team. It removes the effects of the wavelet within the seismic bandwidth. Forces well ties to be made and understood. Reservoir properties are separated from the overburden. May provide quantitative predictions on reservoir properties. Leads to improved Stratigraphic interpretation. Interpretation in the impedance domain is frequently easier than in the seismic domain. Also there is possibility of extending beyond the seismic bandwidth. Inversion Limitations Estimate the frequencies available within seismic by wavelet estimation or spectral analysis. Take the well impedance data and band pass it to the same frequencies as the seismic data. As a rule of thumb use 15 dB down point as limits. If the target is still visible then using Seismic Colored Inversion should be adequate. If not, then need to add frequencies by model assumption. Seismic Attribute It is the quantity obtained or derived from seismic data that can be analyzed in order to improve information that strength be finer in a traditional seismic image, leading to a improved geological or geophysical interpretation of the data. Examples of seismic attributes can include amplitude, measured time, frequency and attenuation and also the combinations of these. Most of the seismic attributes are post-stack, but those that use CMP gathers (such as amplitude versus offset) must be analyzed pre-stack. The initial attributes developed were related to the 1D complex seismic trace and included: envelope amplitude, instantaneous frequency, instantaneous phase and apparent polarity. Acoustic impedance obtained from seismic inversion can also be considered an attribute and was amongst the initially developed. Other attributes commonly used include: coherence, azimuth,
  • 9 dip, instantaneous amplitude, response amplitude, response phase, instantaneous bandwidth, AVO, and spectral decomposition. A seismic attribute that can indicate the presence or absence of hydrocarbons is known as a direct hydrocarbon indicator. Amplitude Attributes: They use the seismic signal amplitude as the basis for their computation. Mean Amplitude: A post-stack attribute that computes the arithmetic mean of the amplitudes of a trace within a specified window. This can be used to observe the trace bias which could indicate the presence of a bright spot. Average Energy: It computes the sum of the squared amplitudes divided by the number of samples within the specified window used. It enables one to map direct hydrocarbon indicators within a zone of interest and also provides a measure of reflectivity RMS (root mean square) Amplitude: A post-stack attribute that computes the square root of the sum of squared amplitudes divided by the number of samples within the specified window used. With the help of this, one can measure reflectivity in order to map direct hydrocarbon indicators in a zone of interest. RMS is quite sensitive to noise as it squares every value within the window. Maximum Magnitude: A post-stack attribute that computes the highest value of the absolute value of the amplitudes within a window. This can be used to map the strongest direct hydrocarbon indicator within a zone of interest. AVO Attributes: AVO stands for Amplitude versus offset. These are pre-stack attributes that have the variation in amplitude of a seismic reflection with varying offset as the basis for their computation, t. These attributes include: AVO gradient, AVO intercept, intercept multiplied by gradient, far minus near, fluid factor, etc. Anelastic Attenuation Factor: Also called as Q .This is a seismic attribute that can be determined from seismic reflection data for both reservoir characterization and advanced seismic processing. Time / Horizon Attributes Coherence: A post-stack attribute that measures the continuity between seismic traces in a specified window along a picked horizon. It is useful to map the lateral extent of a formation. It can also be used to see channels, faults and other discontinuous features. Many software packages compute this attribute along arbitrary time-slices, though it should be used along a specified horizon.
  • 10 Dip: It is a post-stack attribute that computes for each trace, the best fit line (2D) or plane (3D) between its immediate neighbor traces on a horizon and outputs the magnitude of dip (gradient) of the plane or line measured in degrees. The Pseudo paleo-geologic map can be created by this on a horizon slice. Azimuth: This is a post-stack attribute that computes, for each trace, the best fit plane (3D) between its immediate neighbor traces on a horizon and outputs the direction of maximum slope (dip direction) measured in degrees, clockwise from north. This is different from the geological concept of azimuth, which is measured 90° counterclockwise from the dip direction and is equivalent to strike. Curvature: This is a group of post-stack attributes that are computed from the curvature of a specified horizon. These attributes include: magnitude or direction of minimum curvature, magnitude or direction of maximum curvature, magnitude of curvature along the horizon's azimuth (dip) direction, magnitude of curvature along the horizon's strike direction and magnitude of curvature of a contour line along a horizon.