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This case study of an advanced quantitative interpretation workflow is tailored for a seismic multiclient program in the Wolfberry Play of the Midland Basin. Seismic imaging begins by providing a structural interpretation basis, then quantitative interpretation provides 3D elastic and geomechanical attributes through prestack inversion and azimuthal inversion, respectively. This 3D canvas of elastic attributes is combined with petrophysical, mineralogical, geomechanical, and geochemical properties measured at the wells. The challenge of reconciling such data sets with different scales and spatial sampling is overcome using physical, empirical, or statistical relationships within the data. The adjunction of rock data to the 3D elastic attributes provides calibration and validation of the inversion results and quantitative prediction of lithology, facies, porosity, and geochemical properties away from the wells.

This study uses multiple wells with high-quality acoustic and density logs to demonstrate a rock physics workflow for determining dynamic Biots’s coefficient from detailed petrophysical evaluation. One of the important inputs needed for determining dynamic Biots’s coefficient is a detailed interpretation of the rock which has been modeled in this study with a generic stochastic method. In this analysis saturated bulk modulus (Ksat) is assumed to be very close to dry bulk modulus (Kdry) which in unconventional reservoirs, because of the very low porosity, is reasonable. This condition, furthermore, is verified during analysis of the well log curve data.

The Gippsland Basin in South-Eastern Australia is located approximately 200 km east of the city of Melbourne, and remains one of Australia's most prolific oil and gaThe major fields were discovered in the early 1960’s, using images from a coarse 20-km (12 mile) grid of 2D seismic data. There are still extensive areas where no 3D surveys have yet been acquired, and where these do exist, they have an average age of 15 years. s provinces. With extensive infrastructure already in place, and a long history of successful production, CGG has reprocessed existing data sets with the latest high-end technologies and demonstratedthat considerable uplift is possible.

The Wolfcamp reservoir of the Permian Basin has recently generated interest for its potentially vast oil and gas reserves. Imaging this reservoir using seismic data is challenging despite the uncomplicated geology at reservoir depth, because the near-surface in this region is complex. In this work, we apply a modern depth processing flow to data from the Permian Basin and analyze its impact on the resolution of near-surface anomalies and on imaging at the reservoir.

In this paper, we present an integrated study that combines geophysical and geological approaches to perform porosity estimation and populate the reservoir geological model with the estimated property. For pre-salt oilfields, due to the complex porosity distribution in carbonate reservoirs, predicting a reliable porosity is a fundamental step for reservoir modeling.

In order to solve the challenges of imaging the shallow reservoirs of the Barents Sea, CGG, in collaboration with Lundin Norway, have developed an innovative source-over-spread acquisition solution, known as TopSeis. This addresses the lack of near-offset data recorded in conventional towed-streamer acquisition by enabling recording of short and zero-offset data with a split spread, significantly increasing the illumination density of the subsurface. This article looks at the development of this technique with some recent results, including AVO.

In this paper, we look at the HeliFalcon AGG survey conducted in the Aso-Oguni area exploring for geothermal fields, examine the technical challenges presented by the rugged terrains, describe some aspects of the data acquisition and processing, and present the survey results.

The desire to extend all the benefits of broadband 3D data to 4D time-lapse surveys has been hampered by the requirement for repeatability between successive surveys. The use of deep-towed multi-sensor streamers in time-lapse acquisition creates challenges, as the existing baseline surveys will often have been acquired using a shallow-tow streamer. For optimal 4D repeatability, subsequent monitor acquisitions would traditionally be acquired using the same streamer depth as the earlier surveys. We tested recording monitor data at a deeper streamer depth than the baseline survey using multi-sensor streamers, and then redatumming to simulate data recorded at the shallow streamer depth. Following this trial, we went on to acquire three 4D monitor surveys.

Well-tie analysis is a starting point for mapping facies and geology observed at well locations onto seismic cubes. This step is very important for any application that uses seismic and well data together, and can secure more accurate results by increasing consistency between seismic and well log data. A high-quality well-tie is normally considered as the art of an interpreter and is usually practiced through stretch and squeeze of the synthetics log. Many factors can affect the quality of a well-tie, and well log quality is one of the more important ones. However, interpreters and geophysicists focus mainly on seismic and wavelet components and assume well logs as hard data. In practice, well logs are susceptible to different types of errors which may not be fully addressed during the petrophysical work. This paper goes into more detail about this issue and suggests rock physics as an efficient tool for repairing well logs to achieve a better-quality well-tie. Furthermore, different examples from various studies are presented to show the importance of improving well logs using an appropriate rock physics model before well-tie analysis.