Abstract:
Systems and methods for monitoring a crude oil blending process use nuclear magnetic resonance (NMR) sensors which investigate properties of a plurality of crude oil streams that are mixed together to form a crude oil blend. An NMR sensor is also used to investigate the properties of the crude oil blend. The investigated properties may include viscosity. Resulting determinations may be used to control the input streams so that the output stream meets desired criteria. Additional sensors such as spectroscopy sensors, viscometers, and densitometers may be used in conjunction with the NMR sensors.
Abstract:
Methods for improved interpretation of NMR data acquired from industrial samples by simultaneously detecting more than one resonant nucleus without removing the sample from the sensitive volume of the NMR magnet or radio frequency probe are disclosed. In other aspects, the present disclosure provides methods for robust imaging/analysis of spatial distribution of different fluids (e.g., 1H, 23Na, 19F) within a core or reservoir rock. NMR data may be interpreted in real-time during dynamic processes to enable rapid screening, e.g. of enhanced oil recovery techniques and products and/or to provide improved interpretation of well-logs. Measurements of resonant nuclei other than 1H may be performed in the laboratory or downhole with a NMR logging tool. In other aspects, the present disclosure describes a novel kernel function to extract values for underlying parameters that define relaxation time behavior of a quadrupolar nucleus.
Abstract:
Methods for analyzing a reservoir in a formation containing hydrocarbon fluid are described. Information characterizing the formation is collected and applied to a formation simulator that is provided with a modified Darcy's law equation that accounts for at least one of gas adsorption/desorption, various modes of diffusive transport, and non-Darcy flow behavior, and the simulator is used to generate indications of the state of the reservoir and/or the state of production of hydrocarbon fluid from the reservoir. The modified Darcy's law equations are particularly useful in analyzing any type of formation containing any type of hydrocarbon fluid including shale formations containing hydrocarbon gases. According to one embodiment, a dual-porosity shape factor useful in a formation simulator is also provided.
Abstract:
Nuclear magnetic resonance (NMR) methods and apparatus are provided for investigating a sample utilizing NMR pulse sequences. In various embodiments, the NMR pulse sequences have a solid state portion and a line-narrowing portion. In other embodiments, the NMR pulse sequences have a first line-narrowing portion and a second line-narrowing portion where the sequences of the different portions are different. In yet other embodiments, the NMR pulse sequences have a T1 portion and a line-narrowing portion. Processing of detected signals permits determination of characteristics of the sample including, in some cases, a differentiation of multiple components of the sample.
Abstract:
A neural network system includes a first neural network configured to predict a mean value output and epistemic uncertainty of the output given input data, and a second neural network configured to predict total uncertainty of the output of the first neural network. The second neural network is trained to predict total uncertainty of the output of the first neural network given the input data through a training process involving minimizing a cost function that involves differences between a predicted mean value of a geophysical property of a geological formation from the first neural network and a ground-truth value of the geophysical property of the geological formation. The neural network system further includes one or more processors configured to run a software module that determines aleatoric uncertainty of the output of the first neural network based on the epistemic uncertainty of the output and the total uncertainty of the output.
Abstract:
A method and a non-transitory computer readable medium for performing a calculation in a neural network comprise: accepting a data set into the neural network; performing a calculations with the neural network using the data set, wherein the calculations use a loss function and provide an aleatoric and epistemic uncertainty that is correlated to a value; and displaying results of the calculations performed.
Abstract:
Downhole properties of a geological formation may be determined using nuclear magnetic resonance (NMR) measurements obtained by a moving tool. To do so, an interpretation of the NMR data obtained by the moving data may take into account a moving model, characterization, or calibration of the downhole NMR tool. Additionally or alternatively, a partial interpretation mask may exclude interpretation of certain areas of data (e.g., T1-T2 data points or diffusion-T2 data points) that are expected to be less likely to describe downhole materials of interest.
Abstract:
Embodiments herein include a method for characterizing a rock formation sample. The method for characterizing a rock formation sample includes obtaining a plurality of data sets characterizing the rock formation sample. The method further includes training a neural network to generate a computational model. Moreover, the method additionally includes using the plurality of data sets as input to the computational model, wherein the computational model may be implemented by a processor that derives an estimate of permeability of the rock formation sample.
Abstract:
Methods for analyzing a reservoir in a formation containing hydrocarbon fluid are described. Information characterizing the formation is collected and applied to a formation simulator that is provided with a modified Darcy's law equation that ac counts for at least one of gas adsorption/desorption, various modes of diffusive transport, and non-Darcy flow behavior, and the simulator is used to generate indications of the state of the reservoir and/or the state of production of hydrocarbon fluid from the reservoir. The modified Darcy's law equations are particularly useful in analyzing any type of formation containing any type of hydrocarbon fluid including shale formations containing hydrocarbon gases. According to one embodiment, a dual-porosity shape factor useful in a formation simulator is also provided.
Abstract:
A computer-implemented method for reservoir volumetric estimation, a non-transitory computer-readable medium, and a computing system. The method may include running a molecular dynamics simulation of a fluid-rock model of a first reservoir system at a plurality of pressures. The fluid-rock model includes a fluid that is at least partially adsorbed in the first reservoir system at one or more pressures of the plurality of pressures. The method may also include calculating a plurality of isothermal density profiles of the fluid in the first reservoir system, in association with the plurality of pressures using a result of the molecular dynamics simulation. The method may further include determining a first gas accumulation of the fluid in the first reservoir system for the plurality of isothermal density profiles. The first gas accumulation is at least partially a function of a pore surface area of a sample of the first reservoir system.