Schlumberger Technology Corporation

Services Petroliers Schlumberger

Prad Research and Development Limited

Logined B.v.

Georg Zangl

Michael Stundner

Gustavo Nunez

Omer M Gurpinar

Anthony J Fitzpatrick

Radek Pecher

Bulent Balci

Murli Challappa

Andreas Al-Kinani

Thomas Graf

Herwig Fruehbauer

Ruben Saier

Iain Christopher Morrish

Herwig Fruhbauer

Blaine Allen Hollinger

Implementations of pay zone prediction are described. More particularly, apparatus and techniques described herein allow a user to predict pay zones in wells. By accurately predicting pay zones, the user can perforate an existing well at predefined well depths to access hydrocarbon bearing strata while avoiding other undesirable strata (such as water bearing strata). For example, in one possible implementation, well data and syntactic data from a first set of one or more existing wells can be used to create one or more syntactic models. These syntactic models can then be used with water cut and well data from the one or more existing wells to create a pay zone prediction model which can be used with wells outside of the first set of existing wells.

Pay zone prediction

The present invention provides a system and method capable of facilitating the efficient analysis of oilfield data utilizing at least one computer database containing a plurality of stored petroleum engineering operations. In one embodiment, stored petroleum engineering operations may include individual petroleum engineering tasks/calculations, workflows comprising multiple engineering tasks/calculations, and/or third party applications capable of analyzing at least a portion of collected oilfield data. In one embodiment, petroleum engineering operations may be proven in the field, i.e., tested and proven to be accurate under real-world oilfield conditions, prior to storage upon the database. In one embodiment, the present invention provides a graphic user interface adapted to receive customer data and identify stored engineering operations associated thereto. Identified engineering operations stored upon the database may then be displayed and executed according to user instructions and/or predefined execution arrangements.

System and method of facilitating petroleum engineering analysis

Implementations that integrate data-driven modeling and knowledge into self-improving reasoning systems and processes are described. For example, an implementation of a method may include determining at least one recommended action using a reasoning component having a data-driven modeling portion and a knowledge-based portion. Such determining includes integrating one or more determination aspects determined by the data-driven modeling portion, and one or more additional determination aspects determined by the knowledge-based portion.

Methods and systems for self-improving reasoning tools

One or more computer-readable media include computer-executable instructions to instruct a computing system to receive simulation results for future behavior of a reservoir that includes a material production well and a fluid injection site; define a virtual sensor as being located between the material production well and the fluid injection site; determine fluid saturation at the virtual sensor based at least in part on the simulation results; and issue a notification if the fluid saturation at the virtual sensor exceeds a fluid saturation limit. Various other apparatuses, systems, methods, etc., are also disclosed.

Virtual reservoir sensor

To provide a simplified subterranean model of a subterranean structure, a first grid size for the simplified subterranean model is selected, where the first grid size is coarser than a second grid size associated with a detailed subterranean model. The simplified subterranean model is populated with subterranean properties according to the selected first grid size, where multiple realizations of the simplified subterranean model are provided for different sets of values of the subterranean properties. The realizations of the simplified subterranean model are ranked based on comparing outputs of simulations of the realizations with measured data associated with the subterranean structure.

Providing a simplified subterranean model

The invention relates to a method for performing an oilfield operation. The method steps include obtaining oilfield data sets associated with oilfield entities, generating a stochastic database from the oilfield data sets based on an artificial neural network of the oilfield data sets, screening the oilfield data sets to identify candidates from the oilfield entities, wherein the screening is based on the stochastic database, performing a detail evaluation of each candidates, selecting an oilfield entity from the candidates based on the detail evaluation, and performing the oilfield operation for the selected oilfield entity.

Apparatus, method and system for stochastic workflow in oilfield operations

A method of history matching a simulation model is disclosed comprising: (a) defining regions exhibiting similar behavior in the model thereby generating the model having a plurality of regions, each of the plurality of regions exhibiting a similar behavior; (b) introducing historically known input data to the model; (c) generating output data from the model in response to the historically known input data; (d) comparing the output data from the model with a set of historically known output data; (e) adjusting the model when the output data from the model does not correspond to the set of historically known output data, the adjusting step including the step of arithmetically changing each of the regions of the model; and (f) repeating steps (b), (c), (d), and (e) until the output data from the model does correspond to the set of historically known output data.

Method for history matching a simulation model using self organizing maps to generate regions in the simulation model

Computer-based method and system are disclosed for conduction a brownfield assessment. The system/method involves a workflow manager that standardizes the tasks needed to be performed during the brownfield assessment and streamlines the completion of these tasks. The workflow manager incorporates expert knowledge and best practices identified over time for previous brownfield assessments. The expert knowledge and best practices are then applied automatically through operation of the workflow manager. Such an arrangement can result in significantly reduced completion time as well as more consistent deliverables from engineer to engineer and project to project.

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Laxenburg, Austria

Georg Zangl