Systems and methods for probabilistic geology inversion with neural generative models

An apparatus, comprising:

• a memory;
• and
• a processor operatively coupled to the memory, the processor configured to:
• receive input data (1) associated with a geological area and (2) including a plurality of types of input data;
• input the input data into an encoder configured to generate an output (1) based on the input data, (2) representing a compressed version of the input data and (3) that is in a format compatible with a generative network;
• generate first random noise;
• input the output and the first random noise to the generative network to generate a first geological model;
• generate second random noise different than the first random noise;
• input the second random noise, the output, and the first geological model to the generative network to generate a second geological model different than the first geological model;
• generate third random noise;
• input the output and the third random noise to the generative network to generate a third geological model;
• generate a fourth random noise;
• input the fourth random noise, the output, and the third geological model to the generative network to generate a fourth geological model different than the third geological model;
• input the second geological model and not the first geological model into a surrogate model to generate a first surrogate model output associated with the plurality of types of input data;
• compare the first surrogate model output to the input data to determine a first likelihood that the first surrogate model output will occur;
• in response to the first likelihood being within a predetermined acceptable range, include the second geological model in a set of geological models;
• in response to the first likelihood not being within the predetermined acceptable range, refrain from including the second geological model in the set of geological models;
• input the fourth geological model and not the third geological model into the surrogate model to generate a second surrogate model output associated with the plurality of types of input data;
• compare the second surrogate model output to the input data to determine a second likelihood that the second surrogate model output will occur;
• in response to the second likelihood being within the predetermined acceptable range, include the fourth geological model in the set of geological models;
• in response to the second likelihood not being within the predetermined acceptable range, refrain from including the fourth geological model in the set of geological models, the first geological model and the third geological model not included in the set of geological models;
• and
• select, via posterior sampling, at least one geological model from the set of geological models.

A non-transitory, processor-readable medium storing instructions that, when executed by one or more processors, cause the one or more processors to:

• receive input data (1) associated with a geological area and (2) including a plurality of types of input data;
• input the input data into a multi-mode embedding encoder configured to generate an output based on the input data;
• generate first random noise;
• input the output and the first random noise to a generative network to generate a first geological model;
• generate second random noise different than the first random noise;
• input the second random noise, the output, and the first geological model to the generative network to generate a second geological model different than the first geological model;
• generate third random noise;
• input the output and the third random noise to the generative network to generate a third geological model;
• generate a fourth random noise;
• input the fourth random noise, the output, and the third geological model to the generative network to generate a fourth geological model different than the third geological model;
• input the second geological model and not the first geological model into a surrogate model to generate a first surrogate model output associated with the plurality of types of input data;
• compare the first surrogate model output to the input data to determine a first likelihood that the first surrogate model output will occur;
• in response to the first likelihood being within a predetermined acceptable range, include the second geological model in a set of geological models;
• in response to the first likelihood not being within the predetermined acceptable range, refrain from including the second geological model in the set of geological models;
• input the fourth geological model and not the third geological model into the surrogate model to generate a second surrogate model output associated with the plurality of types of input data;
• compare the second surrogate model output to the input data to determine a second likelihood that the second surrogate model output will occur;
• in response to the second likelihood being within the predetermined acceptable range, include the fourth geological model in the set of geological models;
• in response to the second likelihood not being within the predetermined acceptable range, refrain from including the fourth geological model in the set of geological models, the first geological model and the third geological model not included in the set of geological models;
• and
• select, via posterior sampling, at least one geological model from the set of geological models.