Processes for determining formation salinity and saturation

Abstract

Processes for characterizing reservoir formation parameters such as water salinity and water saturation. In some embodiments, the process can include directing a heat impulse into a formation sample that can include a matrix component and a fluid component at an input location. The heat impulse can be allowed to pass through the formation sample such that a matrix impulse forms through the matrix component and a fluid impulse forms through the fluid component. The matrix and fluid impulses can convolve at a measurement location to provide a convolved impulse. A derivative analysis of the convolved impulse can be performed to derive thermal transient measurements. A fluid thermal model can be developed using the thermal transient measurements. The fluid thermal model can be integrated with one or more downhole logs and/or input parameters to create an integrated model. One or more reservoir parameters can be determined from the integrated model.

What is claimed is: 
     
         1 . A process, comprising:
 directing a heat impulse into a formation sample comprising a matrix component and a fluid component at an input location;   allowing the heat impulse to pass through the formation sample such that a matrix impulse forms through the matrix component and a fluid impulse forms through the fluid component, wherein the matrix and fluid impulses convolve at a measurement location to provide a convolved impulse;   performing derivative analysis of the convolved impulse to derive thermal transient measurements;   developing a fluid thermal model using the thermal transient measurements;   integrating the fluid thermal model with one or more downhole logs and/or input parameters to create an integrated model;   determining one or more reservoir parameters from the integrated model; and   directing one or more field operations based on the determined one or more reservoir parameters.   
     
     
         2 . The process of  claim 1 , wherein the heat impulse is a square signal. 
     
     
         3 . The process of  claim 1 , wherein the convolved impulse includes velocity and temperature changes associated with the heat impulse. 
     
     
         4 . The process of  claim 1 , wherein the matrix component includes a mineral matrix. 
     
     
         5 . The process of  claim 1 , wherein the fluid component includes water, a gas, and/or a liquid hydrocarbon. 
     
     
         6 . The process of  claim 1 , wherein integrating the fluid thermal model includes a laboratory measurement of a formation sample obtained from downhole. 
     
     
         7 . The process of  claim 6 , wherein thermal transient measurements are obtained at 0% saturation and 100% saturation to provide end points within the laboratory measurement. 
     
     
         8 . The process of  claim 1 , wherein performing derivative analysis includes validating the convolved impulse using laboratory studies. 
     
     
         9 . The process of  claim 1 , wherein the integrated model includes a semi-supervised machine learning model, neural network, and/or an iterative solver. 
     
     
         10 . The process of  claim 1 , wherein the one or more downhole logs and/or input parameters include borehole logs, core analysis, lithology measurements, porosity measurements, mud parameters, resistivity measurements, nuclear measurements, and/or sonic measurements. 
     
     
         11 . The process of  claim 1 , wherein the one or more reservoir parameters include lithology, porosity, thermal conductivity, thermal capacity, salinity, and/or saturation values. 
     
     
         12 . The process of  claim 1 , wherein the one or more field operations include well location selection, well depth selection, and/or produced water management. 
     
     
         13 . A process, comprising:
 directing a heat impulse into a formation sample comprising a matrix component and a fluid component at an input location;   allowing the heat impulse to pass through the formation sample such that an oil impulse forms through an oil component and a water impulse forms through a water component, wherein the oil and water impulses convolve at a measurement location to provide a convolved impulse;   performing derivative analysis of the convolved impulse to derive thermal transient measurements;   developing a fluid thermal model using the thermal transient measurements;   integrating the fluid thermal model with one or more downhole logs and/or input parameters to create an integrated model;   determining one or more reservoir parameters from the integrated model; and   directing one or more field operations based on the determined one or more reservoir parameters.   
     
     
         14 . The process of  claim 13 , wherein performing derivative analysis includes validating the convolved impulse using laboratory studies. 
     
     
         15 . The process of  claim 13 , wherein developing the fluid thermal model is reservoir specific. 
     
     
         16 . The process of  claim 13 , wherein the integrated model includes a semi-supervised machine learning model, neural network, and/or an iterative solver. 
     
     
         17 . A process, comprising:
 directing a heat impulse into a formation sample comprising a matrix component and a fluid component at an input location;   allowing the heat impulse to pass through the formation sample such that a saturated mineral matrix impulse forms through the saturated mineral matrix component and a water impulse forms through the water component, wherein the saturated mineral matrix and water impulses convolve at a measurement location to provide a convolved impulse;   performing derivative analysis of the convolved impulse to derive thermal transient measurements;   developing a fluid thermal model using the thermal transient measurements;   integrating the fluid thermal model with one or more downhole logs and/or input parameters to create an integrated model;   determining one or more reservoir parameters from the integrated model; and   directing one or more field operations based on the determined one or more reservoir parameters.   
     
     
         18 . The process of  claim 17 , wherein performing derivative analysis includes validating the convolved impulse using laboratory studies. 
     
     
         19 . The process of  claim 17 , wherein developing the fluid thermal model is reservoir specific. 
     
     
         20 . The process of  claim 17 , wherein the integrated model includes a semi-supervised machine learning model, neural network, and/or an iterative solver.