Education Days Buenos Aires 2018

Multiple Short Course Programme

14 - 18 May
Buenos Aires, Argentina
Call for papers


 Date Title  Instructor(s) Duration
 14 - 15 May 2018 Explorational Rock Physics and Seismic Reservoir Prediction Dr Per Avseth
Prof. Dr Tor Arne Johansen
 2 Days
16 - 17 May 2018  New Tools and Approaches in Reservoir Quality Prediction Dr Dave L. Cantrell  2 Days
 18 May 2018  Uncertainty Quantification and Management Dr Dario Grana  1 Day

Courses Descriptions



Explorational Rock Physics and Seismic Reservoir Prediction


Dr Per Avseth (Independent Consultant, Oslo, Norway)
Prof. Dr To
r Arne Johansen (University of Bergen, Bergen, Norway)

Reservoir Characterization – Rock Physics


Course description
The field of rock physics represents the link between qualitative geologic parameters and quantitative geophysical measurements. Increasingly over the last decade, rock physics stands out as a key technology in petroleum geophysics, as it has become an integral part of quantitative seismic interpretation. Ultimately, the application of rock physics tools can reduce exploration risk and improve reservoir forecasting in the petroleum industry.
This course covers fundamentals of rock physics, ranging from basic laboratory and theoretical results to practical recipes that can be immediately applied in the field, presenting qualitative and quantitative tools for understanding and predicting the effects of lithology, pore fluid types and saturation, stress and pore pressure, fractures and temperature on seismic velocity and attenuation.
The importance and benefit of linking rock physics to geologic processes, including depositional and compactional trends as well as tectonic uplift and unloading, are key to this course, which demonstrates in detail how to build so-called rock physics templates that can be used to interpret both well log and seismic inversion data in terms of geological trends and reservoir properties. It is important in exploration and appraisal to extrapolate away from existing wells, taking into account how the depositional environment changes as well as burial depth trends. In this way rock physics can better constrain the geophysical inversion and classification problem in underexplored marginal fields, surrounding satellite areas, or in new frontiers.
In particular, we focus on how rock physics properties, fluid sensitivities and associated seismic signatures change as we go from soft sediments in the shallow subsurface to well consolidated rocks that have undergone more severe mechanical and chemical compaction, and even uplift and brittle deformation. Likewise, we show how seismic amplitudes can change drastically as we go from one depositional environment to another, for instance in a channel-levee complex as we go from central axis to the levee and overbank area.
The course includes practical examples and case studies, as well as suggested workflows, where rock physics models are combined with well log and prestack seismic data, sedimentologic information, inputs from basin modeling and statistical techniques to predict reservoir geology and fluids from seismic amplitudes.

 Participants' profile
The course is intended for geophysicists, geologists and petrophysicists who wish to be involved in quantitative seismic interpretation. The course will focus on how rock physics can be used in exploration but many aspects will also be relevant for production and 4D geophysics.


New Tools and Approaches in Reservoir Quality Prediction

Dr Dave L. Cantrell (Cantrell GeoLogic and Stanford University, USA)

Geology – Geological Modeling

Course description
Reservoir quality prediction has historically been the "holy grail" of reservoir geologists, yet few have been completely successful at achieving this in a truly quantitative fashion. Most oil companies have traditionally based their reservoir quality prediction efforts on geostatistical models that are primarily driven by well and seismic data, usually with some input from qualitative studies of outcrop and observations of modern sedimentary processes. Prediction results from such studies are often less than optimal, especially in areas where data quality is poor and/or data coverage is sparse.

The sheer complexity of factors controlling reservoir quality in the subsurface makes prediction challenging, especially in carbonates. These factors include primary depositional texture and composition, as well as a wide variety of post-depositional modifications that occur to the sediment during and after burial. Developing quantitative tools that allow the prediction of reservoir quality ahead of the bit, and ideally pre-drill, can provide enormous benefits for both exploration and development drilling by reducing the risk associated with exploitation of heterogeneous intervals.

Reservoir quality prediction means different things to different people; this workshop outlines an approach that's based on an understanding of the geological processes that control reservoir quality, and which allows the quantitative prediction of reservoir quality (porosity and permeability) ahead of the bit. To accomplish this, this workshop first provides an overview of the main controls on reservoir quality in both clastic and carbonate rocks, and then presents a new approach to pre-drill reservoir quality prediction that involves the integration of a variety of modelling techniques to understand, quantify and predict the geological processes that control reservoir quality. Since the initial reservoir quality framework is established at the time of deposition by a variety of depositional controls, this workflow uses numerical process models to predict initial reservoir quality; results from these models are then modified via a series of other modeling technologies (compaction models, kinetic cementation models, reaction transport models, etc.) to quantify and predict various diagenetic modifications that have significantly affected reservoir quality in the interval of interest. This approach successfully integrates these two different technologies into one workflow that holistically predicts reservoir quality. Several case histories will be shown in which this approach has been successfully applied.

Participants' profile
The course is designed for geologists, reservoir engineers and technical managers - and for all others looking to enhance their understanding and ability to predict reservoir quality.


Uncertainty Quantification and Management

Dr Dario Grana (University of Wyoming, United States)

Geophysics – Reservoir Characterization


Course description
Reservoir modeling provides a set of techniques to create three-dimensional numerical earth models in terms of elastic, petrophysical and dynamic properties of reservoir rocks. Mathematical/physical models of the reservoir are generally uncertain due to the lack of information, noise in data measurements, approximations and assumptions. The course focuses on the quantification of model uncertainty and its impact on reservoir predictions. It is divided into two main parts:
uncertainty in spatial and time domains, structure, complexity and dimensionality; and
uncertainty management and decision making.
Uncertainty propagation from measured data, through physical models to model predictions will be studied with a focus on seismic data inversion, static reservoir characterization, structural modeling, dynamic fluid simulation, time-lapse monitoring and history matching. The impact of uncertainty on reservoir modeling predictions will be investigated through decision-making theory, to derive strategies to make optimal decisions under different sources of uncertainties. Real case studies will be presented for each topic to illustrate the proposed workflows.

Participants' profile
The course is designed for employees of oil companies in geophysics and reservoir modeling.