Real-time trajectory control during drilling operations

    公开(公告)号:US10801314B2

    公开(公告)日:2020-10-13

    申请号:US15565411

    申请日:2016-12-20

    Abstract: A method may include drilling a deviated wellbore penetrating a subterranean formation according to bottom hole assembly parameters and surface parameters; collecting real-time formation data during drilling; updating a model of the subterranean formation based on the real-time formation data and deriving formation properties therefrom; collecting survey data corresponding to a location of a drill bit in the subterranean formation; deriving a target well path for the drilling based on the model of the subterranean formation; deriving a series of trajectory well paths based on the formation properties, the survey data, the bottom hole assembly parameters, and the surface parameters and uncertainties associated therewith; deriving an actual well path based on the series of trajectory well paths; deriving a deviation between the target well path and the actual well path; and adjusting the bottom hole assembly parameters and the surface parameters to maintain the deviation below a threshold.

    Gridless simulation of a fluvio-deltaic environment

    公开(公告)号:US10324228B2

    公开(公告)日:2019-06-18

    申请号:US14889121

    申请日:2013-10-23

    Abstract: The disclosed embodiments include a method, apparatus, and computer program product for performing gridless simulation of a fluvio-deltaic environment. For example, one disclosed embodiment includes a system that includes at least one processor, and at least one memory coupled to the at least one processor and storing instructions that when executed by the at least one processor performs operations that include generating a set of channel centerlines corresponding to a set of channels that are indicative of flow units in a fluvio-deltaic environment; and generating channel widths for each of the channel centerlines. In one embodiment, the operations for generating the set of channel centerlines of the reservoir include selecting a seed point for each channel, assigning each seed point a direction of propagation, and iteratively generating each channel.

    Basin-to-Reservoir Modeling
    28.
    发明申请
    Basin-to-Reservoir Modeling 有权
    盆地到水库建模

    公开(公告)号:US20150205001A1

    公开(公告)日:2015-07-23

    申请号:US14368363

    申请日:2013-10-15

    CPC classification number: G01V99/005 G06F17/10 G06T17/05

    Abstract: Systems and methods for basin to reservoir modeling to identify any hi-grade drilling targets based on the linking of static and dynamic reservoir rock and fluid properties. Static, present-day, reservoir and field scale description grids or unstructured meshes are transformed into dynamic (through time) simulation grids or unstructured meshes that can subsequently be used for input to dynamic calculators. Basin modeling may be performed at the reservoir scale, providing a link between present-day and the historical process that acted on the rocks and fluids.

    Abstract translation: 基于静态和动态储层岩石和流体性质的连接的盆地到油藏建模的系统和方法,以识别任何高级钻井目标。 静态,现在,水库和场尺度描述网格或非结构化网格被转换为动态(通过时间)模拟网格或非结构化网格,随后可用于输入到动态计算器。 盆地建模可以在水库尺度进行,提供当前日期与作用于岩石和流体的历史过程之间的联系。

    Deep learning based reservoir modeling

    公开(公告)号:US11599790B2

    公开(公告)日:2023-03-07

    申请号:US16614858

    申请日:2017-07-21

    Abstract: Embodiments of the subject technology for deep learning based reservoir modelling provides for receiving input data comprising information associated with one or more well logs in a region of interest. The subject technology determines, based at least in part on the input data, an input feature associated with a first deep neural network (DNN) for predicting a value of a property at a location within the region of interest. Further, the subject technology trains, using the input data and based at least in part on the input feature, the first DNN. The subject technology predicts, using the first DNN, the value of the property at the location in the region of interest. The subject technology utilizes a second DNN that classifies facies based on the predicted property in the region of interest.

    RESERVOIR TURNING BANDS SIMULATION WITH DISTRIBUTED COMPUTING

    公开(公告)号:US20220221615A1

    公开(公告)日:2022-07-14

    申请号:US17595654

    申请日:2020-02-14

    Abstract: A reservoir model for values of a formation property is simulated using a turning bands method with distributed computing. A distributed computing system simulates the reservoir on separate machines in parallel in several stages. First, line distributions are simulated independently on turning bands. The reservoir model is partitioned into tiles and unconditional simulations are run on each tile in parallel using the corresponding simulated turning bands. The unconditional simulations within each tile are conditioned on known formation values to generate conditional simulations. Conditional simulations are aggregated across tiles to create the simulated reservoir model.

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