Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: Selecting hydrocarbon wells for workover. At least some of the illustrative embodiment including: calculating a plurality of present-performance index values for a respectively plurality of wells, each present-performance index value based on a well's performance with respect to the plurality of wells, and each present-performance index value dimensionless; calculating a plurality of future-performance index values for the respective plurality of wells, each future-performance index value based on a well's expected future performance with respect to the plurality of wells, and each future-performance index value dimensionless; combining a present-performance index value and a future-performance index value for a first well to create a first combination index; combining a present-performance index value and a future-performance index value for a second well to create a second combination index; selecting the hydrocarbon well based on the first and second combination indices.

Abstract: Hydrocarbon recovery strategy development. At least some of the illustrative embodiments are methods including: selecting a set of attributes regarding a first undeveloped hydrocarbon reservoir; identifying a first group of developed hydrocarbon reservoirs, the identifying based on the set of attributes of the first undeveloped hydrocarbon reservoir, and the identifying by a computer system; calculating a first set of statistical data based on the first group of developed hydrocarbon reservoirs, the calculating by the computer system; scaling the first set of statistical data in reference to the set of attributes of the first undeveloped hydrocarbon reservoir to create a second set of statistical data, the scaling by the computer system; and implementing at least one hydrocarbon recovery strategy for the first undeveloped hydrocarbon.

Abstract: Selecting hydrocarbon wells for workover. At least some of the illustrative embodiment including: calculating a plurality of present-performance index values for a respectively plurality of wells, each present-performance index value based on a well's performance with respect to the plurality of wells, and each present-performance index value dimensionless; calculating a plurality of future-performance index values for the respective plurality of wells, each future-performance index value based on a well's expected future performance with respect to the plurality of wells, and each future-performance index value dimensionless; combining a present-performance index value and a future-performance index value for a first well to create a first combination index; combining a present-performance index value and a future-performance index value for a second well to create a second combination index; selecting the hydrocarbon well based on the first and second combination indices.

Abstract: Hydrocarbon recovery strategy development. At least some of the illustrative embodiments are methods including: selecting a set of attributes regarding a first undeveloped hydrocarbon reservoir; identifying a first group of developed hydrocarbon reservoirs, the identifying based on the set of attributes of the first undeveloped hydrocarbon reservoir, and the identifying by a computer system; calculating a first set of statistical data based on the first group of developed hydrocarbon reservoirs, the calculating by the computer system; scaling the first set of statistical data in reference to the set of attributes of the first undeveloped hydrocarbon reservoir to create a second set of statistical data, the scaling by the computer system; and implementing at least one hydrocarbon recovery strategy for the first undeveloped hydrocarbon.