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1.发明公开公开(公告)号：US20230272711A1
公开(公告)日：2023-08-31
申请号：US17577463
申请日：2022-01-18
发明人： Cenk Temizel
CPC分类号： E21B49/006 , E21B43/26 , E21B47/06 , E21B49/008 , E21B2200/20 , E21B2200/22
摘要： Systems and methods include a computer-implemented method for optimized injection/production and placement of wells. Stress change correlations are received over space and time for injection/production of fluids to/from a reservoir. A stress distribution of the reservoir is determined using reservoir geomechanical modeling tools and stress change correlations. Fracture growth/propagation behavior for the reservoir is determined using fracture modeling software and geomechanical properties for optimizing treatment. Fracture design and orientation needed for optimum recovery of hydrocarbons are determined by analyzing relationships between fluid injection/withdrawal and geomechanical changes and stress distribution, reservoir geomechanical, and flow characteristics. Changes in the stress distribution in the reservoir are determined through injection/production of fluids. An optimized injection/production and placement of wells are determined using the changes in the stress distribution and the fracture design and orientation. An optimum stress distribution for placement of new wells is determined using the optimized injection/production and placement of wells.
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公开(公告)号：US20230186184A1
公开(公告)日：2023-06-15
申请号：US17546495
申请日：2021-12-09
摘要： Disclosed are methods, systems, and computer-readable medium to perform operations including: identifying historical production data related to a plurality of previously-drilled wells; determining, based on the historical production data, a correlation between productivity index and estimated ultimate recovery (EUR); calculating a first productivity index for a current well; and determining, based on the productivity index of the current well and the correlation, a first EUR of the current well.
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3.发明授权公开(公告)号：US12049820B2
公开(公告)日：2024-07-30
申请号：US17328735
申请日：2021-05-24
CPC分类号： E21B49/0875 , E21B47/10 , E21B43/26 , E21B49/00
摘要： Embodiments herein relate to a technique that may include identifying historical data related to at least one remote well. The technique may further include identifying, based on the historical data, a correlation between gas flow capacity and estimated ultimate recovery (EUR) of the at least one other well. The technique may further include identifying gas flow capacity of a well. The technique may further include predicting, based on the gas flow capacity of the well and the identified correlation between gas flow capacity and EUR of the at least one other well, EUR of the well. The technique may further include operating the well based on the predicted EUR. Other embodiments may be described or claimed.
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公开(公告)号：US20240102371A1
公开(公告)日：2024-03-28
申请号：US17951541
申请日：2022-09-23
发明人： Sohrat Baki , Serkan Dursun , Cenk Temizel
IPC分类号： E21B43/16
CPC分类号： E21B43/16 , E21B2200/20 , E21B2200/22
摘要： Systems and methods include an importance that each of the attributes and features of the well data has on machine learning models. Well data is collected for each well in an unconventional field, including attributes and features of basin data, completion data, and production data. Spatial features are generated for each well in different regions. A combined well features dataset is generated. The dataset maps the well data to the spatial features for each well in the different regions. A training dataset and a testing dataset are generated by splitting the combined dataset. A machine learning model is trained using cross-validation and tuning on the training dataset to predict estimated ultimate recovery (EUR). The performance of a machine learning (EUR) model is evaluated with respect to different regression metrics. An importance that each of the attributes and features of the well data has on machine learning models is determined.
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公开(公告)号：US20230296011A1
公开(公告)日：2023-09-21
申请号：US17698925
申请日：2022-03-18
发明人： Uchenna Odi , Karri Srinivasa Reddy , Cenk Temizel
IPC分类号： E21B44/00
CPC分类号： E21B44/00 , E21B2200/20 , E21B2200/22
摘要： A computer-implemented method for automated decline curve and production analysis using automated production segmentation, empirical modeling, and artificial intelligence. The method includes segmenting historical production data based on a change in a central tendency of a selected segmentation parameter to generate segmented production data. The method also includes forecasting future production data from a last production segment to a terminal decline rate according to a fitted empirical model, a trained artificial intelligence model, or any combinations thereof. The method includes forecasting exponential production data to an economic limit. Further, the method includes calculating an estimated ultimate recovery by summing the historical production data, future production data, and the exponential production data.
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6.发明公开公开(公告)号：US20230184073A1
公开(公告)日：2023-06-15
申请号：US17643993
申请日：2021-12-13
发明人： Cenk Temizel , Hasan O. Yildiz
CPC分类号： E21B43/20 , E21B49/088 , E21B49/0875 , G01V99/005 , E21B2200/22 , E21B2200/20
摘要： Methods and systems for predicting oil production from a reservoir are configured for obtaining production data from a hydrocarbon reservoir, the production data comprising data representing a fractional oil flow; determining, based on the production data, a relationship between the fractional oil flow and cumulative liquid production; identifying, based on the relationship between the fractional oil flow and cumulative liquid production, a post-water breakthrough point; estimating a value for a group parameter at a reference point of the relationship occurring after the post-water breakthrough point; and based on the value of the group parameter, generating a prediction of a future fractional oil flow and a future rate of production of oil from the hydrocarbon reservoir.
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7.发明申请公开(公告)号：US20220372873A1
公开(公告)日：2022-11-24
申请号：US17328735
申请日：2021-05-24
摘要： Embodiments herein relate to a technique that may include identifying historical data related to at least one remote well. The technique may further include identifying, based on the historical data, a correlation between gas flow capacity and estimated ultimate recovery (EUR) of the at least one other well. The technique may further include identifying gas flow capacity of a well. The technique may further include predicting, based on the gas flow capacity of the well and the identified correlation between gas flow capacity and EUR of the at least one other well, EUR of the well. The technique may further include operating the well based on the predicted EUR. Other embodiments may be described or claimed.
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