Abstract: Methods and systems for selecting stimulation candidates in a liquid disposal network of a plurality of wells are disclosed. The method includes obtaining a base disposal pressure and a base injectivity index for each well. The method further includes developing, using a computer processor, a calibrated disposal simulation model for the liquid disposal network, wherein the calibrated disposal simulation model is based, at least, in part, on the base disposal pressure and the base injectivity index. The method still further includes determining, using the computer processor, a predicted disposal pressure and a predicted injectivity index for each well, using a sensitivity analysis of the calibrated disposal simulation model and ranking, using the computer processor, the plurality of wells based, at least in part, on the predicted disposal pressure and the predicted injectivity index for each well.

Abstract: Methods for determination of surface leak rates in an injection well after determining a presence of a surface leak based on visual identification of a leak typically associated with abnormal decrease in surface injection pressure. An injection well performance model is generated based on a reservoir pressure of the injection well, a fluid injection pressure, and properties of an injection fluid. The injection well performance model is calibrated using a shut-in bottomhole pressure and injection data measured prior to the determining of the presence of the surface leak. A production well model is generated from the injection well performance model. For each pressure value between the pressure of the injection well measured at the surface and a shut-in wellhead pressure (SIWHP), the production well model is executed to determine a flow rate of the surface leak.

Abstract: A method may include obtaining wellhead temperature data from a wellhead coupled to a wellbore. The method may further include obtaining production data regarding the wellhead. The method may further include obtaining water cut data from the wellhead. The method may further include calibrating a production model for the wellhead based on the production data and the wellhead temperature data to generate a calibrated production model. The method may further include determining a predicted production rate of the wellhead using the calibrated production model, the water cut data, and flowing wellhead temperature data.

Abstract: Systems and methods include a method for oil-in-water content. A water injection hydraulic simulation model is calibrated using water disposal pressures and rates of a water disposal system of a gas oil separation plant, including generating baseline disposal pressures and disposal rates. The model is updated based on lab results estimating emulsion viscosity at different oil-in-water content levels. A sensitivity analysis is performed to evaluate changes in disposal pressures relative to the baseline in response to changes in water quality based on an oil-in-water emulsion content. Curves of disposal pressures versus disposal rates at different oil-in-water concentrations are generated using the changes in the disposal pressures. Changes in disposal pressures and disposal rates of the water disposal system are recorded, and the changes are compared against the generated curves.

Abstract: A method may include obtaining wellhead temperature data from a wellhead coupled to a wellbore. The method may further include obtaining production data regarding the wellhead. The method may further include obtaining water cut data from the wellhead. The method may further include calibrating a production model for the wellhead based on the production data and the wellhead temperature data to generate a calibrated production model. The method may further include determining a predicted production rate of the wellhead using the calibrated production model, the water cut data, and flowing wellhead temperature data.

Abstract: Methods for determination of surface leak rates in an injection well after determining a presence of a surface leak based on visual identification of a leak typically associated with abnormal decrease in surface injection pressure. An injection well performance model is generated based on a reservoir pressure of the injection well, a fluid injection pressure, and properties of an injection fluid. The injection well performance model is calibrated using a shut-in bottomhole pressure and injection data measured prior to the determining of the presence of the surface leak. A production well model is generated from the injection well performance model. For each pressure value between the pressure of the injection well measured at the surface and a shut-in wellhead pressure (SIWHP), the production well model is executed to determine a flow rate of the surface leak.

Abstract: Calibrated network models for oil production systems are executed using a set of production metrics for a given well. An execution run is initially performed for the given well using a inputs corresponding to a specified time period. Multiple execution runs are performed, iterating on productivity index data for the specified time period, until a simulated production rate converges to a historical production rate corresponding. The productivity index value for the given well at the specified time period is determined based on the converged simulated production rate. The productivity index value represents the rate test conditions at the specified time period. The executing and determining are repeated for additional points in time for the given well to determine productivity index values representing the rate test conditions at respective ones of the additional points in time. A productivity index profile providing productivity index values as a function of time is generated.