Abstract: Provided herein is a device suitable for sweet spot-based machine learning (SSML). There is further provided a processing method in association with completion-based machine learning (COMML). The device can include an input portion configured to receive at least one output signal, the output signal based on at least one production data normalized based on geology and geophysics (G&G)-based data. The device can further include a processing portion coupled to the input portion, the processing portion configured to process the output signal by manner of machine learning-based processing to produce at least one prediction signal, wherein the prediction signal corresponds to at least one visually perceivable graphics-based signal displayable as a three-dimensional (3D) productivity volume for identifying at least one sweet spot location for placement of a structure.

Abstract: There is provided an apparatus which can include a first module which can be configured to receive at least one input signal and/or generate at least one input signal. The input signal(s) can include geology and geophysics (G&G) based data and completion data. Completion data can, for example, be associated with a structure. The first module can be further configured to receive at least one reference signal and/or generate at least one reference signal. The apparatus can further include a second module which can be coupled to the first module. The second module can be configured to process the input signal and the reference signal by manner of normalizing the reference signal based on G&G data and/or normalizing the reference signal based on completion data so as to produce at least one output signal corresponding to at least one normalized reference signal.

Abstract: Systems and methods for improving production from wellbores include providing optimal fracture design parameters based on geomechanical analyses combined with geological, geophysical, and/or petrophysical knowledge. In at least one embodiment, the systems and methods include defining a well direction, defining a fracture spacing, selecting a fracturing fluid system and optimizing a fracture design, such as a complex multi-stage hydraulic fracture design. Such systems and methods can help minimize a learning curve associated with a wellbore or subterranean formation and optimize the hydraulic fracturing operation for a hydrocarbon reservoir.