Iterative determination of decline curve transition in unconventional reservoir modelling

A computer-implemented method for predicting oil and/or gas production at an oil and gas production site, the method comprising:

• receiving input from a user identifying a database (230) containing information about an oil-gas extraction site (OGES), the information originating from sensors at the OGES;
• transmitting production data from the database (230) to a prediction engine (240);
• fitting a first monotonically decreasing function (F1) to the production data over a first time period to generate a first production forecast, using the prediction engine (240);
• iteratively comparing, using the prediction engine (240):
• (1) a predicted production value (Ypred,i) that is a function of the first monotonically decreasing function, with (2) an empirical production value (Yemp,i), to iteratively determine whether the empirical production value is less than the predicted production value;
• if the empirical production value is less than the predicted production value (Yemp,i<Ypred,i), then iteratively updating a parameter of the first monotonically decreasing function to match the empirical production value;
• iteratively comparing, using the prediction engine (240):
• (1) a difference (Δi) between successive values of the updated at least one parameter, with (2) a predetermined error minimization threshold to determine, for each iteration, whether the difference (Δi) between the successive values of the updated at least one parameter is less than the predetermined error minimization threshold;
• if the difference (Δi) is less than the predetermined error minimization threshold, then determining a transition point (T) where the difference between successive parameter values (Δi) is less than the predetermined error minimization threshold;
• and,
• generating a second production forecast over a second time period as a function of a second monotonically decreasing function (F2) different from the first monotonically decreasing function (F1), using the prediction engine (240), wherein a combined production forecast comprises the first production forecast and the second production forecast, the first production forecast transitioning to the second production forecast at the transition point (T) in the combined production forecast.

A computer-implemented method for predicting oil and/or gas production at an oil and gas production site, the method comprising:

• receiving input from a user identifying a database (230) containing information about an oil-gas extraction site (OGES), the information originating from sensors at the OGES;
• transmitting production data from the database (230) to a prediction engine (240);
• fitting a first monotonically decreasing function (F1) to the production data over a first time period to generate a first production forecast, using the prediction engine (240);
• iteratively comparing, using the prediction engine (240):
• (1) a predicted production value (Ypred,i) that is a function of the first monotonically decreasing function, with (2) an empirical production value (Yemp,i), to iteratively determine whether the empirical production value is less than the predicted production value;
• if the empirical production value is less than the predicted production value (Yemp,i<Ypred,i), then iteratively determining a constant-rate decline rate (Dmin,i) of the first monotonically decreasing function that matches the empirical production value by applying a Newton-Raphson bisection method to optimizingly determine the constant-rate decline rate (Dmin,i);
• iteratively comparing, using the prediction engine (240):
• (1) a difference between successive constant-rate decline rates (Δi=Dmin,i−Dmin,i), with (2) a predetermined error minimization threshold (Dthresh), to iteratively determine whether the difference between successive constant-rate decline rates (Δi) is less than the predetermined error minimization threshold;
• if the difference between successive constant-rate decline rates (Δi) is less than the predetermined error minimization threshold (Dmin,i<Dthresh), then determining a transition point (T) where the difference between successive constant-rate decline rates (Δi) is less than the predetermined error minimization threshold;
• generating a second production forecast over a second time period as a function of a second monotonically decreasing function (F2) different from the first monotonically decreasing function (F1), using the prediction engine (240), wherein a combined production forecast comprises the first production forecast and the second production forecast, the first production forecast transitioning to the second production forecast at the transition point (T) in the combined production forecast.