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The most popular seismic attributes fall into broad categories — those that are sensitive to lateral changes in waveform and structure, such as coherence and curvature, and those that are sensitive to lithology and fluid properties — such as AVO and impedance inversion. Unfortunately neither of these two attribute families works well in differentiating the depositional packages characterized by subtle changes in the stratigraphic column or lateral changes in texture. Automatic seismic facies analysis aims to classify similar seismic traces based on amplitude, phase, frequency and other seismic attributes. This paper reviews Kohonen Self Organizing Maps as one of the clustering algorithms that can generate 3D seismic facies volumes and maps using multiple attributes as input. The present area of study is the Mississippian Barnett Shale of the Fort Worth Basin in Texas. The aim of the study is to visualize the variation in shale and possible relationship between these rock types and their seismic expression and try to delineate by passed play after hydraulic fracturing.
Gonzalez, Ezequiel F. (Shell International Exploration and Production) | Gesbert, Stephane (Shell International Exploration and Production) | Hofmann, Ronny (Shell International Exploration and Production)
Using inverted seismic data from a turbidite depositional environment, we show that accounting only for rock types sampled at the wells can lead to biased predictions of the reservoir fluids. The seismic data consists of two volumes resulting from a simultaneous (multi-offset) sparse-spike inversion. As is common in an exploration setting, information from a single well (well logs and petrological analysis) was used to define an initial set of discrete “facies” that characterize both rock type and saturating fluid. Based on our geological understanding of the study area, we augmented this initial model with facies expected in the given depositional environment, yet not sampled by the well. Specifically, the new facies account for variations in both mixture type and proportions of shales and sands. The elastic property distributions of the new facies were modelled using appropriate rock physics models. Finally, a geologically consistent, spatially variant, prior probability of facies occurrence was combined with the data likelihood (per facies) to yield a Bayesian estimation of facies probability at every sample of the inverted seismic data. Accounting for the augmented geological prior in this way, we were able to generate a scenario consistent with all available data, which supports further development of the field. In contrast, using the initial, purely data-driven facies model, Bayesian classification leads to downgrading of the field''s prospectivity. We argue that limited well control in Quantitative Interpretation, especially in an exploration setting, needs to be counterweighted by robust geological prior information, in order to unbiasedly risk geological scenarios.
In this paper, we present a workflow for a Mississipian carbonates characterization case-study integrating post-stack seismic attributes, well-logs porosities, and seismic modeling to explore relating changes in small-scale “lithofacies” properties and/or sub-seismic resolution faulting to key amplitude and coherency 3D seismic attributes. The main objective of this study is to put emphasis on reservoir characterization that is both optimized for and subsequently benefiting from pilot tertiary CO
Unconventional resource plays require that geophysicists redefine the value seismic brings for economic development of these assets. A large part of developing resource plays comes from optimizing engineering practices. Understanding that seismic data contains information regarding resource potential, rock properties, in-situ stress, reservoir pressure and fracture intensity/orientation allows for educated and optimized large scale development plans. The heuristic interpretation templates provided herein outline a method to interpret seismic data for estimated ultimate recovery (EUR) and the important physical properties for hydraulic fracturing all of which provide insight for optimizing completion efforts.
This work presents a noise attenuation technique based upon applying a sparsity constraint to a time-frequency transform. It is demonstrated that the solution obtained from applying the sparsity constraint rather than the more common minimum norm constraint produces a superior noise attenuated signal. The sparsity constrained transformation is achieved by finding a sparse representation of the input data in terms of a dictionary of complex Ricker wavelets. The utilization of a complex wavelet dictionary possesses the advantage that signals with arbitrary phase can be represented with enhanced sparsity. Examples with synthetic and real microseismicity data illustrate the capacity of the technique to attenuate ambient noise in microseismic records with low signal-to-noise ratio.
Controlled source electromagnetic transmitters create highly geometric coupled electric and magnetic vector fields that propagate in a way that is dependent on both the orientation of the transmitter and electrical conductivity distribution. There may be a good case for using cross well controlled source electromagnetic methods for monitoring injection of CO
Choi, Yunseok (King Abdullah University of Science and Technology) | Alkhalifah, Tariq (King Abdullah University of Science and Technology) | Saragiotis, Christos (King Abdullah University of Science and Technology)
First-arrival picking has long suffered from cycle skipping, especially when the first arrival is contaminated with noise or have experienced complex near surface phenomena. We propose a new algorithm for automatic picking of first arrivals using an approach based on unwrapping the phase. We unwrap the phase by taking the derivative of the Fourier-transformed wavefield with respect to the angular frequency and isolate its amplitude component. To do so, we first apply a damping function to the seismic trace, calculate the derivative of the wavefield with respect to the angular frequency, divide the derivative of wavefield by the wavefield itself, and finally take its imaginary part. We compare our derivative approach to the logarithmic one and show that the derivative approach does not suffer from the phase wrapping or cycle-skipping effects. Numerical examples show that our automatic picking algorithm gives convergent and reliable results for the noise-free synthetic data and noisy field data.
Vidal, Carlos Almagro (Delft University of Technology) | van der Neut, Joost (Delft University of Technology) | Draganov, Deyan (Delft University of Technology) | Drijkoningen, Guy (Delft University of Technology) | Wapenaar, Kees (Delft University of Technology)
Seismic interferometry (SI) enables the retrieval of virtual-shot records at the location of receivers. In the case of passive SI, no active sources are required for the retrieval of the reflection response of the subsurface, but ambient-noise recording only. It is the illumination features of the recorded ambient noise that determine the resulting retrieved response. Such characteristics, like geometry and signature of the noise sources, together with the complexity of the medium, are responsible for the quality of the retrieved virtual-shot events and the length of the recorded noise. To retrieve body-wave reflections, one would need to correlate body-wave noise from relatively deeper sources. A source of such noise might be the regional seismicity. In regions with noticeable human presence, the dominant noise sources will be located at or close to the surface. In the later case, the noise will be dominated by surface waves and consequently also the retrieved virtual-shot records will contain retrieved surface waves drowning retrieved reflections. We present a method for carrying out an illumination diagnostics of the recorded ambient noise using the correlation results from the recorded noise. We explain the method using an example from a passive dataset recorded at Annerveen, Northern Netherlands, and show how this diagnostic tool helps improve the retrieval of reflections.
Yang, Jian (Oudeh Petroleum Company) | Gou, Xuemin (Oudeh Petroleum Company) | Hilmi, Nabil (Oudeh Petroleum Company) | Xia, Rick (Oudeh Petroleum Company) | Sun, Xiangyang (LandOcean Energy Services Co., Ltd.) | Li, Peng (LandOcean Energy Services Co., Ltd.) | Wu, Qiang (LandOcean Energy Services Co., Ltd.) | Liu, Hua (LandOcean Energy Services Co., Ltd.)
The factures play a major role in the production of low permeability heavy oil carbonate reservoirs with a complex oil-water contact. Fracture swarms significantly improve local connectivity and provide pore space which increase oil production; whereas large deeply rooted fractures into aquifer increase the risk of early and unexpected water breakthrough. In this paper, an integrated approach for fracture characterization and prediction is applied by using FMI logs, post-stack seismic attributes and pre-stack anisotropy. FMI log is well known as a direct detection for fractures. It is mostly used to identify fractures features and to classify fracture types at wellbore. Geological research are made by using post-stack seismic attributes and well data to find the controlling factors of fracture network in this area. The relationship between fault system and fracture network is considered here. Other factors which may influence fracture distribution such as lithology, fluid, related stress field, etc, are studied too. To find accurate fracture orientation and density, a method based on pre-stack anisotropy analysis is also applied. Four azimuths are used in seismic anisotropy analysis after correlation. Fracture orientations are derived from the anisotropy analysis according to seismic forward modeling. Fracture density is quantified with attenuation attributes and amplitude attributes. A case study in Tishrine West (TW) Oilfield, Northeast Syria is presented. The result shows that, fracture distribution is controlled by multiple factor, fault system has close relationship with fracture network. High fracture density area in the model is correlated with high producibility.
The increasing need for continuous reservoir monitoring is one of the primary concerns to the oil industry to improve the hydrocarbon recovery factor and production efficiency. Several monitoring scenarios with geophysical methods can be derived including surface and borehole-based methods and their combinations. One is a surface electric current dipole and a vertical electric borehole receiver which has the strongest coupling in detecting the water flood front changes and is easy to implement. The surface-to-borehole electromagnetic if combined with seismic can give excellent resolving capabilities. A modeling study was performed to generate several results based on the given model. This is to support feasibility studies as well as to determine survey acquisition parameters. A 3-layer model was used with a hydrocarbon reservoir in the second layer. The optimum transmitter offset was determined by the modeling result and the value was used for the rest of the experiment. The resistivity of the hydrocarbon reservoir was also varied to observe the received vertical electric field. A time lapse study is relevant for the reservoir monitoring. We built and simulated 3-D model to apply this technology to real reservoirs. In combinations with reservoir simulator results it predicts the outcome of potential surveys. The model is then translated to time lapse fluid changes in order to design the survey layout such that we can get a maximum response.