Adam Koesoemadinata

Seismic Reservoir Characterization In Marcellus Shale

The Middle Devonian Marcellus shale that extends from Ohio and West Virginia, northeast into Maryland, Pennsylvania and New York, is believed to hold in excess of a thousand trillion ft of natural gas. High-quality surface seismic data and top-of-the-line processing are essential to characterize these reservoirs and the overburden formations for safe and cost-effective drilling. A workflow comprising data acquisition and processing to prestack seismic inversion and lithofacies classification for characterizing the shale reservoirs is presented. The key elements in this workflow are dense point-receiver data acquisition and processing in the point-receiver domain. A small data set acquired with a proprietary point-receiver system was available to demonstrate the benefits of this methodology. The data were in an area in New York, where the Marcellus formation is known to exist.

A global acoustic impedance inversion for porosity and lithology prediction in northern Gulf of Mexico

Summary Poststack seismic inversion based on a multitrace global optimization method was conducted as part of a large study that covered about 10,200 km 2 , consisting of 502 Outer Continental Shelf blocks, located primarily in the northern Gulf of Mexico, offshore Louisiana. Considering that seismic inversion was carried out over such a huge area with a long time window (7 s two-way time), lateral and vertical variation of the seismic data were the main concerns. Seismic data conditioning to provide consistent, zero-phase wavelets over the whole volume was done iteratively with wavelet extraction and analysis at well locations. The vertical variability of wavelets due to frequency attenuation and amplitude decays with depth were also incorporated in the inversion process. The principle objective of the seismic inversion was to transform seismic reflection data into quantitative petrophysical properties. Acoustic impedance is commonly used for porosity prediction. Over the study area, the correlation between acoustic impedance and porosity is very poor because the impedance varies substantially vertically and spatially due to varying sedimentation rates and sediment compaction. An alternative transformation was applied to use relative acoustic impedance to predict effective porosity, ϕe, and volume fraction of shale, Vc. The results show that the inverted relative acoustic impedance and predicted ϕe and Vc are in reasonable match with wells over the entire study area. The use of relative acoustic impedance efficiently produced reliable ϕe and Vc. Aside from its limitations, such as disregarding the effects of fluid variations and complex lithological variations on the porosity/impedance relation, the method provides a reliable screening tool for seismic exploration. More quantitative details of the petrophysical properties can be obtained through a more sophisticated inversion method in the prestack domain.

Extracting Density Anomalies From Converted Waves: a Case Study In the Gulf of Mexico

Density information is very difficult to obtain using conventional PP reflection data. This is because the AVO effects are not sensitive to density changes in PP reflection equation (Lines, 1999). Moreover, Aki-Richards or Zoeppritz equations of reflected and refracted energy partitioning are not stable when the incident angles reach the critical angles where most of the density information is found in PP and PS reflections. This makes it even more difficult to get reliable density information from PP inversion, even including long-offset data.

Impact of stress‐induced anisotropy caused by salt bodies on depth imaging: a synthetic case study

As anisotropic depth imaging is widely used in the industry, anisotropic velocity models are routinely being constructed and applied. However, the degree of accuracy of the anisotropic velocity model needed to correctly position the horizons is not well defined. To that end, we tested four anisotropic parameter estimation scenarios and performed depth imaging using a realistic synthetic sedimentary seismic data that included an irregularly shaped salt body. Although similar images derived from the data using those four different anisotropic input models were obtained, a quantitative analysis indicates that systematic differences do exist. They enable us to relate the degree of accuracy needed in the image to the effort needed to build the anisotropic velocity model.

Quantifying Reservoir Properties of the East Texas Woodbine Through Rock Physics And Multiattribute Seismic Inversion

Multiattribute seismic inversion (MASI) is a newly developed prestack inversion technique for inverting seismic data into elastic parameter attributes. The method integrates several major technologies (Roberts, et al., 2005), including AVO processing and analysis, well-log editing and calibration, prestack waveform inversion (PSWI) (Mallick, et al., 2000), wavelet processing, and poststack inversion. The outputs are high-resolution absolute acoustic and shear impedance and density volumes consistent with the seismic data and the well-log data. The inverted elastic parameter volumes are used for detailed interpretation of lithofacies and pore-fluid content in the subsurface. Combined with rock physics modeling and rock property mapping through LithoCube (Bachrach, et al., 2004) and joint porosity-saturation inversion (Bachrach and Dutta, 2004), the method provides a powerful tool for quantitative reservoir description and characterization. The results are the most-probable litho-class, porosity, and saturation with uncertainties of prediction at every sample point in the 3-D volume. Recently we applied this method to identify and characterize Woodbine sandstone reservoirs in an onshore East Texas field.

Converted-wave elastic impedance inversion in practice: A case study in the Gulf of Mexico

The 2D line under study is one in a multiline grid of a largescale, 2D-4C OBC, long-offset (up to 10,000 m) acquisition program that covers a large number of OCS blocks in the northern Gulf of Mexico. Figures 1 and 2 show the PP and PS image of this line, with a gamma ray log overlaying on the sections. We see that seismic imaging near the target zone has been hampered by a severe gas cloud effect in the PP data, while the PS data have much better quality in and below the gas cloud. In the prestack domain, the signal-to-noise ratio (SNR) of the PS gathers near the reservoir is also much higher than the SNR of the PP gathers (not shown here due to space limitation).