PowerPoint Presentation: Ravva | Innovating Development Seismic Interpretation Seismic data is indispensable for exploration and development to understand the subsurface structures. 3D seismic data is free from off plane reflection, increases imaging to a great extent and provides denser sampling of the subsurface strata & structures. Seismic interpretation provides valuable inputs for optimal field development by precisely mapping subsurface structures and suitably placing producer and injector locations. Many seismic surveys, 2D and 3D were acquired in the Ravva block area of which, the 3D steamer 1990 was used for phase I field development. In 2000, Ocean Bottom Cable (OBC) 3D seismic was acquired and the data was used for the subsequent infill development of the field. Seismic attributes like Amplitude Verus Offset (AVO) and impedance inversion and rock property volumes like total porosity, clay volume and fluid saturation, calibrated with well information gives insights for a better placement of infill wells and extension of field life. The advanced seismic interpretation tools use interactive workstations for large amounts of seismic data by applying techniques like manual picking, interpolation, autotracking, voxel tracking and horizon slicing. Well-ties are adopted to characterise the seismic signatures of the reservoir intervals through construction of synthetic seismograms. In Ravva, with the availability of the well data, excellent well to seismic ties were established. The identified seismic events in Ravva data are correlated blockwide in the 3D volume along with faults to improve the structural framework and to position the infill producers optimally. In addition to providing excellent structural images, the surface slices in the zone of interest provide vital stratigraphic information for the characterisation of the reservoir. A Rock Physics Analysis was conducted to understand the log and seismic responses of the reservoir sands and shales. The ultimate goal of the analysis was to gain insights into the petrophysical properties of reservoir such as lithology, porosity, and fluid content through AVO analysis or seismic inversion. This included depth-trend analysis, cross-plot analysis, fluid substitution modeling, AVO interface modeling, 2D wedge modeling and offset synthetic modeling. AVO classification was performed with modeled responses. In Ravva, the Miocene oil bearing sand has been classified as class II/III responses with good AVO gradient. Based on the Rock Physics analysis, AVO inversion was carried out to generate P-Impedance, SImpedance, Poisson ratio, Fluid Factor, Lambda and Mu. The other attributes such as coherency, spectral decomposition, stochastic rock properties, and enhanced restricted gradient were also used for the reservoir characterisation. The stochastic rock properties were used for the detailed reservoir characterisation work. It has provided a technically definable method to populate the properties between and away from the well points. The method has helped to increase the confidence level to estimate the in-place volumes of Ravva. The effective visualisation of 3D seismic data volumes is of great value to geoscientists, as it brings greater flexibility and power for maximum impact on G&G workflows. The visualisation environment allows the display of different volumes and attributes simultaneously, which enhances the quality of interpretation.
PowerPoint Presentation: Ravva | Innovating Development The power of 3D visualisation comes from volume rendering, which uses colour and opacity to filter seismic data attributes for selective display in three dimensions. Opacity tool allows the user to pick and choose which amplitudes to display within volumes. The 3D visualisation also includes interpretation of seismic attributes related to rock and fluid properties and time-lapse seismic interpretation to trace the movement of fluids within the reservoir during production. This technique was used extensively in Ravva and has helped to visualise the geobodies and channel geometries in Pliocene and late Miocene strata. The identified geobodies were analysed for hydrocarbon potential in the Ravva block. Seismic Attribute Analysis Ravva block has many seismic volumes generated over a period of 15 years. Amplititudes versus Offset (AVO) attributes, saturation, effective porosity, Continuous Wavelet Transform (CWT), Coherence/ Variance and Enhanced Restricted Gradient (ERG), etc. are some of the volumes, which have been generated using state of the art technology. The attributes are used to the best of their potential to decipher, delineate, and characterise the producing reservoirs as well as the exploration targets. Seismic attribute analysis radically changes exploration for hydrocarbons. It facilitates extracting the maximum amount of value from the seismic data by providing more detail on the subtle lithological variations of the reservoir. They are extracted with reference to the top of the marker or extracted window to decipher the geological information and understand the distribution of reservoir facies for placement of additional development locations to recover more oil and gas from the reservoirs or to add more resources by suitable exploration well locations in a virgin area. Most of the attributes routinely run on 3D seismic data are Root Mean Square (RMS) Amplitudes, Maximum of Positive and Negative Amplitudes, or Instantaneous Amplitudes extracted from the correlated horizon. The attached figure is an example of RMS amplitude extraction attribute from Pre-Stack Time Migration (PSTM) from the reservoir Miocene section, which delineated the extent of the reservoir sands and subsequently was proved successful by drilling. Multi trace seismic attributes are extracted using more than one seismic trace as input and provide information about lateral variations in the seismic data. Seismic Coherence is a measure of the trace-to-trace similarity of the seismic waveform within an analysis window over the entire volume of the data set. The Coherence volume/variance cube helps in the interpretation of the variations in the faults and sedimentary facies, and the delineation of the sedimentary facies zones within favourable hydrocarbon reservoirs. The coherence slices are helpful in the delineation and distribution of faults, and thus, significant in the exploration and development of oil and gas.The variance cube was generated for the Ravva block to study the variance among the seismic traces in the lower late Miocene sequence. The variance cube was flattened with reference to the mapped horizon and horizon slices were generated. The horizon slice corresponding to1500 msec had clearly brought out the channel morphology with associated faulting at this level.
PowerPoint Presentation: Ravva | Innovating Development Spectral Decomposition of Seismic Data Spectral decomposition is an invaluable tool to identify the channel geometry and associated geological features, especially in a fluvial environment, where morphology is the key indicator to understand the depositional environment. There are primarily two types of software applications for Spectral Decomposition:-1) SWFFT and 2) CWT. Of late, CWT has been widely used for its frequency localisation aspects of the signal. CWT is the analysis of the frequency of the data at local level and does not require a window to carry out the analysis. However, the data generated varies with the frequency of the volumes and is blended to highlight the anomalies associated with the sequence to understand the morphological evidences to arrive at the probable geometry of the reservoir sands in order to place the development locations. Extensive studies were carried out in the Ravva Block to bring out the morphology of the discontinued sands, which are hydrocarbons bearing in lower late Miocene sequence. This was addressed by subjecting PSTM volume to CWT of frequencies ranging from 8 Hz to 42 Hz, thus, extracting the geological information pertaining to the reservoir sands. The analysis clearly brought out the channel geometry and gave substantial insights into the probable depositional environment of these sands as well as the extent of the hydrocarbon bearing sands. This helped in understanding the opportunities available for these sands to be of primary/secondary targets for exploration/development. AVO Amplitude versus offset or AVO analysis is perhaps the most commonly utilised direct hydrocarbon indicator in exploration reflection seismology. Hydrocarbon related ‘AVO anomalies’ may show increasing or decreasing amplitude variation with offset. Conversely, brinesaturated ‘background’ rocks may show increasing or decreasing AVO. The AVO interpretation is facilitated by cross plotting AVO intercept (A) and gradient (B). Under a variety of reasonable geological circumstances, in a well-defined ‘background’ trend. ‘AVO anomalies’ are properly viewed as deviations from this background and maybe related to hydrocarbons or lithologic factors. AVO anomalies have been observed prominently in the main reservoirs of the Ravva block. The various attribute volumes like Lambda-Dlambda, Mu, Rho volumes have been adequately characterised by the fluid effects. The attributes derived from these volumes have successfully demonstrated the efficacy of AVO and have been used for delineation and subsequent placement of the wells. ERG Attribute AVOS derived cross plotting techniques have been invaluable in identifying hydrocarbon bearing sands. Apart from the cross-plotting, forward modelling studies show the response of amplitudes with offset when substituted with different fluids, and on calibrating the responses of hydrocarbons and brine fluids. This phenomenon is seen very clearly on angle stacks processed from full stack responses of the seismic data. Qualitative attributes of these angled stacks will give fluid response with different angle stacks. It has been observed that ultra far (angles beyond 50 ) stacks indicate bright response for hydrocarbon bearing sands whereas near angle and mid angle stacks illuminate the effects of the brine fluids. ERG attribute is generated using these brightening aspects by simultaneously illuminating the bodies of hydrocarbon as well as those filled with brine. This attribute was generated after forward modelling as well as understanding the effects of AVO vis-à-vis the reservoir rocks of middle Miocene and sands of lower late Miocene sequences. After delineating the channel morphology of the sands, the fluid characterisation is carried out by generating ERG attribute. The attribute identifies the probable locations of hydrocarbon filled geobodies in the sequence for further volume estimates to be candidates for exploratory/development drilling.