Resistivity log conditioning and flow type prediction in gas bearing carbonate reservoirs

Abstract

Methods for identify zones within a carbonate reservoir with (a) high porosity and high resistivity or (b) low porosity and high resistivity as potential gas-producing zones may use both resistivity data and effective porosity data where the resistivity data is conditioned before integration with the effective porosity data. For example, a method may include conditioning deep resistivity data for a plurality of zones of a subterranean formation, thereby producing conditioned deep resistivity data; integrating the conditioned deep resistivity data with effective porosity data for the plurality of zones, thereby producing a flow index curve for each of the plurality of zones; and identifying one or more potential gas-producing zones from the plurality of zones based on the flow index curve.

The invention claimed is: 
     
         1 . A method comprising:
 conditioning deep resistivity data for a plurality of zones of a subterranean formation, thereby producing conditioned deep resistivity data;   integrating the conditioned deep resistivity data with effective porosity data for the plurality of zones, thereby producing a flow index curve for each of the plurality of zones; and   identifying one or more potential gas-producing zones from the plurality of zones based on the flow index curve.   
     
     
         2 . The method of  claim 1 , wherein the conditioning of the deep resistivity data comprises:
 producing a cross-plot of the deep resistivity data and the effective porosity data, wherein data points in a low effective porosity, high deep resistivity region of the cross-plot are conditioned.   
     
     
         3 . The method of  claim 1 , wherein the integrating of the conditioned deep resistivity data with the effective porosity data comprises: (conditioned deep resistivity)*(effective porosity) n  where 1<n≤10. 
     
     
         4 . The method of  claim 1 , wherein the integrating of the conditioned deep resistivity data with the effective porosity data comprises: value=(conditioned deep resistivity)*(effective porosity) n  where 1<n≤10 and the flow index curve is the values normalized. 
     
     
         5 . The method of  claim 1 , wherein the identifying the one or more potential gas-producing zones comprises:
 classifying each of the plurality of zones by a flow type based on the flow index curve.   
     
     
         6 . The method of  claim 1 , wherein the identifying the one or more potential gas-producing zones comprises:
 classifying each of the plurality of zones by a flow type based on the flow index curve; and   applying the flow type of the plurality of zones as an input to a model of the subterranean formation.   
     
     
         7 . The method of  claim 1 , wherein the identifying the one or more potential gas-producing zones comprises:
 applying the flow index curve for each of the plurality of zones as an input to a model of the subterranean formation.   
     
     
         8 . The method of  claim 1 , wherein the integrating of the conditioned deep resistivity data with the effective porosity data comprises a normalizing step such that values in the flow index curve range from 0 to 1, and wherein the identifying of the one or more potential gas-producing zones comprises:
 classifying the plurality of zones based as Flow Type 1 with a flow index of greater than or equal to 0.5, Flow Type 2 with the flow index between 0.2 and 0.5, and Flow Type 3 with the flow index less than or equal to 0.2.   
     
     
         9 . The method of  claim 8  further comprising:
 performing an under balanced coil tube drilling operation on at least one of the plurality of zones classified as the Flow Type 1. 
 
     
     
         10 . The method of  claim 8  further comprising:
 performing a stimulation operation on at least one of the plurality of zones classified as the Flow Type 2. 
 
     
     
         11 . The method of  claim 8  further comprising:
 not performing a stimulation operation on at least one of the plurality of zones classified as the Flow Type 3. 
 
     
     
         12 . A method comprising:
 conditioning deep resistivity data for a plurality of zones of a subterranean formation, thereby producing conditioned deep resistivity data, wherein the conditioning involves producing a cross-plot of the deep resistivity data and the effective porosity data, wherein data points in a low effective porosity, high deep resistivity region of the cross-plot are conditioned;   integrating the conditioned deep resistivity data with effective porosity data for the plurality of zones, thereby producing a flow index curve for each of the plurality of zones, wherein the integrating comprises (a) value=(conditioned deep resistivity)*(effective porosity) n  where 1<n≤10 and optionally (b) normalizing the values, wherein the flow index curve is either based on the values or the normalized values;   identifying one or more potential gas-producing zones from the plurality of zones based on the flow index curve; and   performing a wellbore operation on at least one of the one or more potential gas-producing zones.   
     
     
         13 . A machine-readable storage medium having stored thereon a computer program for identifying one or more potential gas-producing zones, the computer program comprising a routine of set instructions for causing the machine to perform the steps of:
 conditioning deep resistivity data for a plurality of zones of a subterranean formation, thereby producing conditioned deep resistivity data;   integrating the conditioned deep resistivity data with effective porosity data for the plurality of zones, thereby producing a flow index curve for each of the plurality of zones; and   identifying the one or more potential gas-producing zones from the plurality of zones based on the flow index curve.   
     
     
         14 . The machine-readable storage medium of  claim 13 , wherein the conditioning of the deep resistivity data comprises:
 producing a cross-plot of the deep resistivity data and the effective porosity data, wherein data points in a low effective porosity, high deep resistivity region of the cross-plot are conditioned.   
     
     
         15 . The machine-readable storage medium of  claim 13 , wherein the integrating of the conditioned deep resistivity data with the effective porosity data comprises: (conditioned deep resistivity)*(effective porosity) n  where 1<n≤10. 
     
     
         16 . The machine-readable storage medium of  claim 13 , wherein the identifying the one or more potential gas-producing zones comprises:
 classifying each of the plurality of zones by a flow type based on the flow index curve.   
     
     
         17 . The machine-readable storage medium of  claim 13 , wherein the identifying the one or more potential gas-producing zones comprises:
 classifying each of the plurality of zones by a flow type based on the flow index curve; and   applying the flow type of the plurality of zones as an input to a model of the subterranean formation.   
     
     
         18 . The machine-readable storage medium of  claim 13 , wherein the identifying the one or more potential gas-producing zones comprises:
 applying the flow index curve for each of the plurality of zones as an input to a model of the subterranean formation.   
     
     
         19 . The machine-readable storage medium of  claim 13 , wherein the integrating of the conditioned deep resistivity data with the effective porosity data comprises a normalizing step such that values in the flow index curve range from 0 to 1, and wherein the identifying of the one or more potential gas-producing zones comprises:
 classifying the plurality of zones based as Flow Type 1 with a flow index of greater than or equal to 0.5, Flow Type 2 with the flow index between 0.2 and 0.5, and Flow Type 3 with the flow index less than or equal to 0.2.   
     
     
         20 . The machine-readable storage medium of  claim 19 , wherein the set of instructions further causing the machine to provide a recommendation regarding:
 (a) performing an under balanced coil tube drilling operation on at least one of the plurality of zones classified as the Flow Type 1;   (b) performing a stimulation operation on at least one of the plurality of zones classified as the Flow Type 2;   (c) not performing a stimulation operation on at least one of the plurality of zones classified as the Flow Type 3; or   (d) any combination of two or more of (a), (b), and (c).