# US 2016/0259088 A1 · Estimating Well Production Performance In Fractured Reservoir Systems > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2016/0259088 A1 - Document ID: US20160259088A1 - Status: Published application - Kind: A1 - Application number: 14/648,852 - Filed: 2014-08-01 - Published: 2016-09-08 - Earliest claimed: 2014-08-01 - Assignees: Landmark Graphics Corporation - Applicants: Landmark Graphics Corporation - Inventors: Gustavo Carvajal; Vitaly Khoriakov; Andrey Filppov; Marko Maucec; Arturo Diaz; Steven Knabe - Web page: https://patentgrep.com/patent/US20160259088A1 ## CPC - E21B 41/00: Equipment or details not covered by groups E21B15/00 - E21B40/00 - E21B 47/06: Measuring temperature or pressure - E21B 49/00: Testing the nature of borehole walls; Formation testing; Methods or apparatus for obtaining samples of soil or well fluids, specially adapted to earth drilling or wells - E21B 43/26: by forming crevices or fractures - G01V 2210/1234: Hydrocarbon reservoir, e.g. spontaneous or induced fracturing - G01V 2210/61: Analysis by combining or comparing a seismic data set with other data - E21B: EARTH OR ROCK DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS - G01V: GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS (means for indicating the location of accidentally buried, e.g. snow-buried, persons A63B29/02) ## Abstract Systems and methods for estimating well production performance in fractured reservoir systems using real-time down-hole temperature and stress information from advanced monitoring techniques. ## Claims ### Claim 1 A method for identifying poor fracture conductivity in fractured reservoir systems to use in refracturing, which comprises: a) sampling an average effective fracture length from a distribution of average effective fracture lengths; b) selecting current pressure and temperature profiles over a length of each fracture stage; c) performing history matching to determine a misfit using the current pressure and temperature profiles, the distribution of average effective fracture lengths, the sampled average effective fracture length and a computer processor; d) updating a static well model using the current pressure and temperature profiles, the distribution of average effective fracture lengths and the sampled average effective fracture length for the static well model; e) calculating a fracture conductivity for each fracture stage; f) selecting pressure and temperature profiles for a predetermined period of time over the length of each fracture stage; g) performing history matching using at least one pressure and temperature profile from the pressure and temperature profiles selected for the predetermined period of time, the distribution of any effective fracture lengths, the sampled average effective fracture length and the computer processor; h) updating the updated static well model, which represents a new updated static well model, using the at least one pressure and temperature profile from the pressure and temperature profiles selected for the predetermined period of time, the distribution of average effective fracture lengths and the sampled average effective fracture length for the updated static well model; i) calculating a Reynolds number for each fracture stage based on the new updated static well model; and j) identifying each fracture stage with poor fracture conductivity using at least one of the fracture conductivity and the Reynolds number calculated for each fracture stage. ### Claim 2 (depends on 1) The method of claim 1, further comprising refracturing a reservoir system based on a fracture stage with at least one of the fracture conductivity less than about 1 md.ft. and the Reynolds number greater than about 1. ### Claim 3 (depends on 1) The method of claim 1, further comprising repeating steps a)-c) until the misfit is acceptable. ### Claim 4 (depends on 1) The method of claim 1, wherein the fracture conductivity for each fracture stage is calculated using a total flow rate and a mass flow rate for each fracture stage. ### Claim 5 (depends on 3) The method of claim 3, wherein the misfit is minimized with each iteration of steps a)-c). ### Claim 6 (depends on 3) The method of claim 3, wherein the misfit is acceptable at less than about 10% deviation. ### Claim 7 (depends on 1) The method of claim 1, wherein the static well model is represented by standard reservoir properties, complex reservoir properties, complex fracture network properties, production data profiles and standard well completion and simulation properties. ### Claim 8 A non-transitory program carrier device tangibly carrying computer-executable instructions for identifying poor fracture conductivity in fractured reservoir systems to use in refracturing, the instructions being executable to implement: a) sampling an average effective fracture length from a distribution of average effective fracture lengths; b) selecting current pressure and temperature profiles over a length of each fracture stage; c) performing history matching to determine a misfit using the current pressure and temperature profiles, the distribution of average effective fracture lengths, the sampled average effective fracture length; d) updating a static well model using the current pressure and temperature profiles, the distribution of average effective fracture lengths and the sampled average effective fracture length for the static well model; e) calculating a fracture conductivity for each fracture stage; f) selecting pressure and temperature profiles for a predetermined period of time over the length of each fracture stage; g) performing history matching using at least one pressure and temperature profile from the pressure and temperature profiles selected for the predetermined period of time, the distribution of any effective fracture lengths, the sampled average effective fracture length; h) updating the updated static well model, which represents a new updated static well model, using the at least one pressure and temperature profile from the pressure and temperature profiles selected for the predetermined period of time, the distribution of average effective fracture lengths and the sampled average effective fracture length for the updated static well model; i) calculating a Reynolds number for each fracture stage based on the new updated static well model; and j) identifying each fracture stage with poor fracture conductivity using at least one of the fracture conductivity and the Reynolds number calculated for each fracture stage. ### Claim 9 (depends on 8) The program carrier device of claim 8, further comprising refracturing a reservoir system based on a fracture stage with at least one of the fracture conductivity less than about 1 md.ft. and the Reynolds number greater than about 1. ### Claim 10 (depends on 8) The program carrier device of claim 8, further comprising repeating steps a)-c) until the misfit is acceptable. ### Claim 11 (depends on 8) The program carrier device of claim 8, wherein the fracture conductivity for each fracture stage is calculated using a total flow rate and a mass flow rate for each fracture stage. ### Claim 12 (depends on 10) The program carrier device of claim 10, wherein the misfit is minimized with each iteration of steps a)-c). ### Claim 13 (depends on 10) The program carrier device of claim 10, wherein the misfit is acceptable at less than about 10% deviation. ### Claim 14 (depends on 8) The program carrier device of claim 8, wherein the static well model is represented by standard reservoir properties, complex reservoir properties, complex fracture network properties, production data profiles and standard well completion and simulation properties. ### Claim 15 A method for identifying poor fracture conductivity in fractured reservoir systems to use in refracturing, which comprises: a) selecting acoustic profiles for a predetermined period of time over a length of each fracture stage; b) calculating a compressional velocity using at least one of the acoustic profiles; c) identifying a main lithology of an acoustic medium represented by the acoustic profiles and a related Gardner coefficient; d) calculating an effective stress using the compressional velocity and the Gardner coefficient; e) calculating a fracture conductivity for each fracture stage using the effective stress and a computer processor; and f) identifying each fracture stage with poor fracture conductivity. ### Claim 16 (depends on 15) The method of claim 15, further comprising refracturing a reservoir system based on a fracture stage with at least one of the fracture conductivity less than about 1 md.ft. and the Reynolds number greater than about 1. ### Claim 17 (depends on 15) The method of claim 15, wherein the main lithology of the acoustic medium is identified using a lithology log generated in a static well model. ### Claim 18 A non-transitory program carrier device tangibly carrying computer-executable instructions for identifying poor fracture conductivity in fractured reservoir systems to use in refracturing, the instructions being executable to implement: a) selecting acoustic profiles for a predetermined period of time over a length of each fracture stage; b) calculating a compressional velocity using at least one of the acoustic profiles; c) identifying a main lithology of an acoustic medium represented by the acoustic profiles and a related Gardner coefficient; d) calculating an effective stress using the compressional velocity and the Gardner coefficient; e) calculating a fracture conductivity for each fracture stage using the effective stress; and f) identifying each fracture stage with poor fracture conductivity. ### Claim 19 (depends on 18) The program carrier device of claim 18, further comprising refracturing a reservoir system based on a fracture stage with at least one of the fracture conductivity less than about 1 md.ft. and the Reynolds number greater than about 1. ### Claim 20 (depends on 18) The program carrier device of claim 18, wherein the main lithology of the acoustic medium is identified using a lithology log generated in a static well model.