A computer-implemented method for time lapse monitoring of a target feature within a rock formation , the method comprising: generating a starting model (S10) for time lapse monitoring from initial data relating to said rock formation prior to a start of time lapse; calculating a response (S12) of the starting model for a plurality of electromagnetic sources and a plurality of electromagnetic receivers using a numerical algorithm; creating one or more different scenario models (S13) that hypothesize how subsurface electromagnetic properties of said rock formation will be changing over time, each said scenario model corresponding to a different time; calculating a response (S14) of the one or more scenario models for the plurality of electromagnetic sources and a plurality of electromagnetic receivers using the same numerical algorithm applied in calculating the response of the starting model; calculating (S15) an optimal set of data weighted electromagnetic source parameters that maximize a difference between the response of the starting model and the response of the one or more scenario models, wherein the data weighted electromagnetic source includes the plurality of electromagnetic sources and wherein an electromagnetic field contribution from each electromagnetic source is weighted according to the set of data weighted electromagnetic source parameters; analyzing (S16) a real time lapse data set relating to said rock formation by applying the calculated optimal set of data weighted electromagnetic source parameters to the real time lapse data set; and calculating (S17) a difference between the real time lapse data set and the initial data set. generating a starting model (S10) for time lapse monitoring from initial data relating to said rock formation prior to a start of time lapse; calculating a response (S12) of the starting model for a plurality of electromagnetic sources and a plurality of electromagnetic receivers using a numerical algorithm; creating one or more different scenario models (S13) that hypothesize how subsurface electromagnetic properties of said rock formation will be changing over time, each said scenario model corresponding to a different time; calculating a response (S14) of the one or more scenario models for the plurality of electromagnetic sources and a plurality of electromagnetic receivers using the same numerical algorithm applied in calculating the response of the starting model; calculating (S15) an optimal set of data weighted electromagnetic source parameters that maximize a difference between the response of the starting model and the response of the one or more scenario models, wherein the data weighted electromagnetic source includes the plurality of electromagnetic sources and wherein an electromagnetic field contribution from each electromagnetic source is weighted according to the set of data weighted electromagnetic source parameters; analyzing (S16) a real time lapse data set relating to said rock formation by applying the calculated optimal set of data weighted electromagnetic source parameters to the real time lapse data set; and calculating (S17) a difference between the real time lapse data set and the initial data set. <EOS>