IP Library › Granted Patent US 12,560,741
Granted Patent B2
US 12,560,741 · App. 17/712,820 · Granted Feb 24, 2026

System and method to develop naturally fractured hydrocarbon reservoirs using a fracture density index

Inventors: Karla Patricia Olvera Carranza (Dhahran, SA); Otto Meza Camargo (Dhahran, SA)
Assignee: Saudi Arabian Oil Company
G01V20/00E21B43/16E21B43/26E21B2200/20G01V2210/624G01V2210/646
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12,560,741
App. No.
17/712,820
Granted
Feb 24, 2026
Kind
B2
Abstract

Hydrocarbon reservoir development that includes determining, based on fracture data, a two-dimensional (2D) fracture model including fracture lines representing locations of fractures in the reservoir, determining, based on the lines, a fracture density index (FDI) map including FDI values for cells representing the reservoir, including, for each cell, determining a FDI value based on proximity to the fracture lines, determining a circulation loss (CL) map including CL values for the cells, including, for each cell, determining a CL value based on proximity of the cell to locations of circulation loss events in the hydrocarbon reservoir, determining, based on the FDI map and the CL map, a correlation of FDI to CL for the reservoir, and drilling a hydrocarbon well based on the correlation.

Claims (45)

1 . A method of developing a hydrocarbon reservoir, the method comprising:

determining, based on fracture data for the hydrocarbon reservoir obtained from a first well accessing the hydrocarbon reservoir, a two-dimensional (2D) fracture model comprising fracture lines representing locations of fractures in formation rock of the hydrocarbon reservoir;

determining, based on the lines of the 2D fracture model, a fracture density index (FDI) map comprising FDI values for cells of a 2D grid of cells representing the hydrocarbon reservoir, the determining of the FDI map comprising, for each cell of the grid of cells, determining a FDI value for the cell based on a proximity of the cell to the location of the fracture lines;

determining a circulation loss (CL) map comprising circulation loss values for the cells of the grid of cells representing the hydrocarbon reservoir, the determining of the circulation loss map comprising, for each cell of the grid of cells, determining a CL value for the cell based on a proximity of the cell to locations of circulation loss events in the hydrocarbon reservoir, wherein determining the CL value comprises:

determining a 2D circulation loss model comprising circulation loss points representing locations of circulation loss events observed during drilling of wells in the hydrocarbon reservoir, wherein the CL value for the cell is determined based on a proximity of the cell to the circulation loss points;

determining, based on the FDI map and the CL map, a correlation of fracture density index value to circulation loss values for the hydrocarbon reservoir;

determining, based on the correlation, a location in the hydrocarbon reservoir for a second well, the location having a fracture density less than the location of the first well and avoiding circulation losses; and

drilling the second well at the location to access hydrocarbons in the hydrocarbon reservoir.

2 . The method of claim 1 , wherein the fracture lines of the 2D fracture model correspond to fracture planes of a 3D fracture model that represent natural fractures in the formation rock of the hydrocarbon reservoir.

3 . The method of claim 1 , wherein the FDI values for the cells are determined by way of a kernel density method.

4 . The method of claim 1 , wherein the FDI values for the cells are determined by way of a line density method.

5 . The method of claim 1 , wherein determining the correlation of fracture density index to circulation losses comprises fitting a line to a plot of FDI-CL value pairs for respective cells of the 2D grid of cells representing the hydrocarbon reservoir, wherein the correlation is defined by the line.

6 . The method of claim 1 , further comprising:

generating a FDI model indicating FDI values across the area of the reservoir corresponding to the grid of cells and locations of circulation loss events observed during drilling of wells in the hydrocarbon reservoir,

wherein the location of the second well to be drilled is determined based on the FDI model.

7 . A non-transitory computer readable storage medium comprising program instructions stored thereon that are executable by a processor to perform the following operations for developing a hydrocarbon reservoir:

determining, based on fracture data for the hydrocarbon reservoir obtained from a first well accessing the hydrocarbon reservoir, a two-dimensional (2D) fracture model comprising fracture lines representing locations of fractures in formation rock of the hydrocarbon reservoir;

determining, based on the lines of the 2D fracture model, a fracture density index (FDI) map comprising FDI values for cells of a 2D grid of cells representing the hydrocarbon reservoir, the determining of the FDI map comprising, for each cell of the grid of cells, determining a FDI value for the cell based on a proximity of the cell to the location of the fracture lines;

determining a circulation loss (CL) map comprising circulation loss values for the cells of the grid of cells representing the hydrocarbon reservoir, the determining of the circulation loss map comprising, for each cell of the grid of cells, determining a CL value for the cell based on a proximity of the cell to locations of circulation loss events in the hydrocarbon reservoir, wherein determining the CL value comprises:

determining a 2D circulation loss model comprising circulation loss points representing locations of circulation loss events observed during drilling of wells in the hydrocarbon reservoir, wherein the CL value for the cell is determined based on a proximity of the cell to the circulation loss points;

determining, based on the FDI map and the CL map, a correlation of fracture density index value to circulation loss values for the hydrocarbon reservoir;

determining, based on the correlation, a location in the hydrocarbon reservoir for a second well, the location having a fracture density less than the location of the first well and avoiding circulation losses; and

controlling drilling of the second well at the location to access hydrocarbons in the hydrocarbon reservoir.

8 . The medium of claim 7 , wherein the fracture lines of the 2D fracture model correspond to fracture planes of a 3D fracture model that represent natural fractures in the formation rock of the hydrocarbon reservoir.

9 . The medium of claim 7 , wherein the FDI values for the cells are determined by way of a kernel density method.

10 . The medium of claim 7 , wherein the FDI values for the cells are determined by way of a line density method.

11 . The medium of claim 7 , wherein determining the correlation of fracture density index to circulation losses comprises fitting a line to a plot of FDI-CL value pairs for respective cells of the 2D grid of cells representing the hydrocarbon reservoir, wherein the correlation is defined by the line.

12 . The medium of claim 7 , the operations further comprising:

generating a FDI model indicating FDI values across the area of the reservoir corresponding to the 2D grid of cells and locations of circulation loss events observed during drilling of wells in the hydrocarbon reservoir,

wherein the location of the second well to be drilled is determined based on the FDI model.

13 . A hydrocarbon reservoir development system comprising:

a hydrocarbon reservoir control system comprising non-transitory computer readable storage medium comprising program instructions stored thereon that are executable by a processor to perform the following operations for developing a hydrocarbon reservoir:

determining, based on fracture data for the hydrocarbon reservoir obtained from a first well accessing the hydrocarbon reservoir, a two-dimensional (2D) fracture model comprising fracture lines representing locations of fractures in formation rock of the hydrocarbon reservoir;

determining, based on the lines of the 2D fracture model, a fracture density index (FDI) map comprising FDI values for cells of a 2D grid of cells representing the hydrocarbon reservoir, the determining of the FDI map comprising, for each cell of the grid of cells, determining a FDI value for the cell based on a proximity of the cell to the location of the fracture lines;

determining a circulation loss (CL) map comprising circulation loss values for the cells of the grid of cells representing the hydrocarbon reservoir, the determining of the circulation loss map comprising, for each cell of the grid of cells, determining a CL value for the cell based on a proximity of the cell to locations of circulation loss events in the hydrocarbon reservoir, wherein determining the CL value comprises:

determining a 2D circulation loss model comprising circulation loss points representing locations of circulation loss events observed during drilling of wells in the hydrocarbon reservoir, wherein the CL value for the cell is determined based on a proximity of the cell to the circulation loss points;

determining, based on the FDI map and the CL map, a correlation of fracture density index value to circulation loss values for the hydrocarbon reservoir;

determining, based on the correlation, a location in the hydrocarbon reservoir for a second well, the location having a fracture density less than the location of the first well and avoiding circulation losses; and

controlling drilling of the second well at the location to access hydrocarbons in the hydrocarbon reservoir.

14 . The system of claim 13 , wherein the fracture lines of the 2D fracture model correspond to fracture planes of a 3D fracture model that represent natural fractures in the formation rock of the hydrocarbon reservoir.

15 . The system of claim 13 , wherein the FDI values for the cells are determined by way of a kernel density method or a line density method.

16 . The system of claim 13 , wherein determining the correlation of fracture density index to circulation losses comprises fitting a line to a plot of FDI-CL value pairs for respective cells of the 2D grid of cells representing the hydrocarbon reservoir, wherein the correlation is defined by the line.

17 . The system of claim 13 , the operations further comprising:

generating a FDI model indicating FDI values across the area of the reservoir corresponding to the grid of cells and locations of circulation loss events observed during drilling of wells in the hydrocarbon reservoir,

wherein the location of the second well to be drilled is determined based on the FDI model.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 4, 2022
From: OLVERA CARRANZA, KARLA PATRICIA; CAMARGO, OTTO MEZA
To: SAUDI ARABIAN OIL COMPANY
Reel/Frame 059492/0767 →
Continuity (1)
Related Publication 20230313649A1 · Oct 5, 2023
References Cited (257)
US 6502037B1 · Jorgensen et al. · 2002 [cited by applicant]
US 6705398B2 · Weng · 2004 [cited by applicant]
US 6904365B2 · Bratton et al. · 2005 [cited by applicant]
US 7025138B2 · Kurkjian et al. · 2006 [cited by applicant]
US 7042802B2 · Sinha · 2006 [cited by applicant]
US 7337660B2 · Ibrahim et al. · 2008 [cited by applicant]
US 7457194B2 · Prioul et al. · 2008 [cited by applicant]
US 7526385B2 · Sayers · 2009 [cited by applicant]
US 7562278B2 · Lyakh et al. · 2009 [cited by applicant]
US 7565278B2 · Li et al. · 2009 [cited by applicant]
US 7679993B2 · Sayers · 2010 [cited by applicant]
US 7707018B2 · Shaw · 2010 [cited by applicant]
US 7941307B2 · Symington et al. · 2011 [cited by applicant]
US 8010294B2 · Dorn et al. · 2011 [cited by applicant]
US 8024124B2 · Sayers · 2011 [cited by applicant]
US 8041510B2 · Dasgupta · 2011 [cited by applicant]
US 8078405B2 · Delorme · 2011 [cited by applicant]
US 8121792B2 · Hsu et al. · 2012 [cited by applicant]
US 8204727B2 · Dean et al. · 2012 [cited by applicant]
US 8301427B2 · Souche et al. · 2012 [cited by applicant]
US 8374836B2 · Yogeswaren · 2013 [cited by applicant]
US 8498848B2 · Habashy et al. · 2013 [cited by applicant]
US 8619500B2 · Gray · 2013 [cited by applicant]
US 8756016B2 · Tabanou et al. · 2014 [cited by applicant]
US 8780671B2 · Sayers · 2014 [cited by applicant]
US 8898046B2 · Moos et al. · 2014 [cited by applicant]
US 9022140B2 · Marx et al. · 2015 [cited by applicant]
US 9062545B2 · Roberts et al. · 2015 [cited by applicant]
US 9063251B2 · Moos · 2015 [cited by applicant]
US 9068448B2 · Hui et al. · 2015 [cited by applicant]
US 9110190B2 · Yogeswaren · 2015 [cited by applicant]
US 9152745B2 · Glinsky · 2015 [cited by applicant]
US 9305121B2 · Yao et al. · 2016 [cited by applicant]
US 9390204B2 · Bowen et al. · 2016 [cited by applicant]
US 9417348B2 · Lin · 2016 [cited by applicant]
US 9435192B2 · Lawrence et al. · 2016 [cited by applicant]
US 9465140B2 · Crawford et al. · 2016 [cited by applicant]
US 9618652B2 · Weng et al. · 2017 [cited by applicant]
US 9677393B2 · Morris · 2017 [cited by applicant]
US 9846260B2 · Mallet · 2017 [cited by applicant]
US 9988895B2 · Roussel et al. · 2018 [cited by applicant]
US 10001003B2 · Dusseault et al. · 2018 [cited by applicant]
US 10101498B2 · Berard et al. · 2018 [cited by applicant]
US 10190406B2 · Holland et al. · 2019 [cited by applicant]
US 10302785B2 · Dirksen et al. · 2019 [cited by applicant]
US 10310137B1 · Mallet · 2019 [cited by applicant]
US 10352145B2 · Maxwell et al. · 2019 [cited by applicant]
US 10422208B2 · Weng et al. · 2019 [cited by applicant]
US 10465509B2 · Yao et al. · 2019 [cited by applicant]
US 10528681B2 · Yogeswaren · 2020 [cited by applicant]
US 10563493B2 · Ganguly et al. · 2020 [cited by applicant]
US 10571605B2 · Crawford et al. · 2020 [cited by applicant]
US 10572611B2 · Huang et al. · 2020 [cited by applicant]
US 10607043B2 · Camargo et al. · 2020 [cited by applicant]
US 10724346B2 · Eftekhari Far et al. · 2020 [cited by applicant]
US 10760416B2 · Weng et al. · 2020 [cited by applicant]
US 10787887B2 · Pankaj et al. · 2020 [cited by applicant]
US 10846447B2 · Myers et al. · 2020 [cited by applicant]
US 10853533B2 · Plateaux et al. · 2020 [cited by applicant]
US 10920538B2 · Rodriguez Herrera et al. · 2021 [cited by applicant]
US 10920552B2 · Rodriguez Herrera et al. · 2021 [cited by applicant]
US 11098582B1 · Camargo et al. · 2021 [cited by applicant]
US 11180975B2 · Renaudeau et al. · 2021 [cited by applicant]
US 11313994B2 · Salman et al. · 2022 [cited by applicant]
US 11434759B2 · Awan et al. · 2022 [cited by applicant]
US 11599790B2 · Pandey et al. · 2023 [cited by applicant]
US 11834931B2 · Guillot · 2023 [cited by examiner]
US 20070100594A1 · Lamoureux-Var et al. · 2007 [cited by applicant]
US 20070255545A1 · Pita et al. · 2007 [cited by applicant]
US 20070272407A1 · Lehnman et al. · 2007 [cited by applicant]
US 20080071505A1 · Huang et al. · 2008 [cited by applicant]
US 20090319243A1 · Suarez-Rivera et al. · 2009 [cited by applicant]
US 20100191470A1 · Tabanou et al. · 2010 [cited by applicant]
US 20100250216A1 · Narr et al. · 2010 [cited by applicant]
US 20120072188A1 · Maerten et al. · 2012 [cited by applicant]
US 20130046524A1 · Gathogo et al. · 2013 [cited by applicant]
US 20130054207A1 · Souche · 2013 [cited by examiner]
US 20130297269A1 · Davies et al. · 2013 [cited by applicant]
US 20130299241A1 · Alberty et al. · 2013 [cited by applicant]
US 20140358510A1 · Sarkar et al. · 2014 [cited by applicant]
US 20150129211A1 · Dusseault et al. · 2015 [cited by applicant]
US 20150276979A1 · Hugot et al. · 2015 [cited by applicant]
US 20160222765A1 · Nooruddin et al. · 2016 [cited by applicant]
US 20160245939A1 · Williams · 2016 [cited by applicant]
US 20160266274A1 · Alqam et al. · 2016 [cited by applicant]
US 20160266278A1 · Holderby et al. · 2016 [cited by applicant]
US 20160281498A1 · Nguyen et al. · 2016 [cited by applicant]
US 20170051598A1 · Ouenes · 2017 [cited by applicant]
US 20170132339A1 · Umholtz et al. · 2017 [cited by applicant]
US 20170145793A1 · Ouenes · 2017 [cited by applicant]
US 20170176228A1 · Elisabeth · 2017 [cited by applicant]
US 20170205531A1 · Berard et al. · 2017 [cited by applicant]
US 20170254909A1 · Agharazi · 2017 [cited by applicant]
US 20170316128A1 · Huang et al. · 2017 [cited by applicant]
US 20180203146A1 · Den Boer et al. · 2018 [cited by applicant]
US 20190080122A1 · Camargo et al. · 2019 [cited by applicant]
US 20190345815A1 · Mishra · 2019 [cited by applicant]
US 20200056460A1 · Isaev et al. · 2020 [cited by applicant]
US 20200095858A1 · Bouaouaja et al. · 2020 [cited by applicant]
US 20200141215A1 · Crews et al. · 2020 [cited by applicant]
US 20200225382A1 · Mallet et al. · 2020 [cited by applicant]
US 20200225383A1 · Mallet et al. · 2020 [cited by applicant]
US 20200326322A1 · Farrukh Hamza · 2020 [cited by applicant]
US 20210054736A1 · Moos et al. · 2021 [cited by applicant]
US 20210102461A1 · Kumar et al. · 2021 [cited by applicant]
US 20210132246A1 · Liu et al. · 2021 [cited by applicant]
US 20210140313A1 · Busetti · 2021 [cited by applicant]
US 20210222518A1 · Bardy et al. · 2021 [cited by applicant]
US 20210350052A1 · Alwahtani et al. · 2021 [cited by applicant]
US 20220018245A1 · Coenen · 2022 [cited by applicant]
US 20220291418A1 · Noufal · 2022 [cited by applicant]
US 20230012429A1 · Camargo et al. · 2023 [cited by applicant]
US 20230084141A1 · Camargo et al. · 2023 [cited by applicant]
US 20230333278A1 · Camargo et al. · 2023 [cited by applicant]
AU 2013374225B2 · 2014 [cited by applicant]
AU 2018267575B9 · 2018 [cited by applicant]
BR PI1003737A2 · 2012 [cited by applicant]
CA 2778313A1 · 2011 [cited by applicant]
CA 2904008A1 · 2014 [cited by applicant]
CA 2932670A1 · 2017 [cited by applicant]
CA 3043231A1 · 2018 [cited by applicant]
CN 102042010B · 2014 [cited by applicant]
CN 102788994B · 2015 [cited by applicant]
CN 104459775B · 2015 [cited by applicant]
CN 104500050A · 2015 [cited by applicant]
CN 105403929A · 2016 [cited by applicant]
CN 105484741A · 2016 [cited by applicant]
CN 103064114B · 2016 [cited by applicant]
CN 106285659A · 2017 [cited by applicant]
CN 104992468B · 2018 [cited by applicant]
CN 105134156B · 2018 [cited by applicant]
CN 108331555A · 2018 [cited by applicant]
CN 107578343B · 2020 [cited by applicant]
CN 107577831B · 2020 [cited by applicant]
CN 110850057B · 2021 [cited by applicant]
CN 112253103B · 2021 [cited by applicant]
CN 112065351B · 2021 [cited by applicant]
CN 113534291A · 2021 [cited by applicant]
CN 109102180B · 2021 [cited by applicant]
CN 112526107B · 2021 [cited by applicant]
CN 109388817B · 2022 [cited by applicant]
CN 114153002A · 2022 [cited by applicant]
CN 115166853A · 2022 [cited by applicant]
EP 3118758A1 · 2017 [cited by applicant]
EP 2179134B1 · 2018 [cited by applicant]
EP 3074957B1 · 2022 [cited by applicant]
EP 4042211 · 2022 [cited by applicant]
FR 2979016A · 2013 [cited by applicant]
KR 101620506B1 · 2016 [cited by applicant]
KR 102111207B1 · 2020 [cited by applicant]
RU 2404359C2 · 2010 [cited by applicant]
WO 2010111398A2 · 2010 [cited by applicant]
WO 2013169256A1 · 2013 [cited by applicant]
WO 2015168417A1 · 2015 [cited by applicant]
WO 2016122792A1 · 2016 [cited by applicant]
WO 2016198894A2 · 2016 [cited by applicant]
WO 2016209822A1 · 2016 [cited by applicant]
WO 2017019388A1 · 2017 [cited by applicant]
WO 2017216594A1 · 2017 [cited by applicant]
WO 2019238451A1 · 2019 [cited by applicant]
WO 2020167282A1 · 2020 [cited by applicant]
WO 2020198210A1 · 2020 [cited by applicant]
WO 2021108439A1 · 2021 [cited by applicant]
WO 2021236877A1 · 2021 [cited by applicant]
WO 2023130074A1 · 2023 [cited by applicant]
Wickham, J., et al. “Geomechanics of Fracture Density” Unconventional Resources Tech. Conf., URTeC control ID No. 1619745 (2013) (Year: 2013). [cited by examiner]
Al-Nutaifi, A.M., et al. “Wellbore Instability Analysis for Highly Fractured Carbonate Gas Reservoir from Geomechanics Prospective, Saudi Arabia Case Study” Int'l Petroleum Tech. Conf. (2014) (Year: 2014). [cited by examiner]
Zastoupil, L.B. “A Geomechanical Equation for Fracture Density/Brittleness and Comparisons with a Mineralogical Brittleness Index” Masters Thesis, U. Texas at Arlington (2015) (Year: 2015). [cited by examiner]
Wehunt, D. “Stochastic 2D Well Path Assessments for Naturally Fractured Carbonate Reservoirs” Society of Petroleum Engineers, SPE-180468-MS (2016) (Year: 2016). [cited by examiner]
Maucec, M., et al. “New Approach to History Matching of Simulation Models with Discrete Fracture Networks” Int'l Petroleum Tech. Conf. (2020) (Year: 2020). [cited by examiner]
Fischer, K. et al.; “Generating and Calibrating 3D Geomechanical Reservoir Models” 75th EAGE Conference and Exhibition incorporating SPE EUROPEC 2013, London UK, Jun. 10-13, 2013; pp. 1-5. [cited by applicant]
Ahmadi, Mohammad Ali; “Toward Reliable Model for Prediction Drilling Fluid Density at Wellbore Conditions: A LSSVM Model” Neurocomputing, vol. 211, Oct. 26, 2016; pp. 143-149. [cited by applicant]
Aksenov, A.A. et al.; “Prediction of Distribution of Hydrogen Sulfide in Oil-Gas Basins” Petroleum Geology: A digest of Russian literature on Petroleum Geology; vol. 16 (1979), No. 10 (October); pp. 439-441. [cited by applicant]
Al-Hawas, Khalid et al.; Delineation of fracture anisotropy signatures in Wudayhi Field by azimuthal seismic data; The Leading Edge, Interpreter's Corner, Dec. 2003; pp. 1202-1211. [cited by applicant]
Aldrich, Jeffrey B. et al.; “‘Sweet Spot’ Identification and Optimization in Unconventional Reservoirs” Search and Discovery Article #80644 (2018); pp. 1-6. [cited by applicant]
ArcGIS; “How Kernel Density works” available as of Jan. 28, 22 at: https://desktop.arcgis.com/en/arcmap/10.6/tools/spatial-analyst-toolbox/how-kernel-density-works.htm; pp. 1-3. [cited by applicant]
ArcGIS Pro 2.8; “An overview of the Density toolset” available as of Apr. 4, 2022 at: https://pro.arcgis.com/en/pro-app/2.8/tool-reference/spatial-analyst/an-overview-of-the-density-tools.htm; p. 1. [cited by applicant]
ArcGIS Pro 2.8; “How Kernel Density Works” Available as of Mar. 14, 2022 at: https://pro.arcgis.com/en/pro-app/2.8/tool-reference/spatial-analyst/how-kernel-density-works.htm; pp. 1-6. [cited by applicant]
ArcGIS Pro 2.8; “Kernel Density (Spatial Analyst)” available as of Mar. 14, 2022 at: https://pro.arcgis.com/en/pro-app/2.8/tool-reference/spatial-analyst/kernel-density.htm; pp. 1-5. [cited by applicant]
ArcGIS Pro 2.8; “Line Density (Spatial Analyst)” available as of Apr. 4, 2022 at: https://pro.arcgis.com/en/pro-app/2.8/tool-reference/spatial-analyst/line-density.htm; pp. 1-6. [cited by applicant]
ArcGIS Pro 2.8; “Point Density (Spatial Analyst)” available as of Apr. 4, 2022 at: https://pro.arcgis.com/en/pro-app/2.8/tool-reference/spatial-analyst/point-density.htm; pp. 1-7. [cited by applicant]
Barton, Colleen A. et al.; “Fluid flow along potentially active faults in crystalline rock” Geology; Aug. 1995; v.23; No. 8; pp. 683-686. [cited by applicant]
Bisdom, Kevin et al.; “A geometrically based method for predicting stress-induced fracture aperture and flow in discrete fracture networks” AAPG Bulletin v. 100, No. 7 (Jul. 2016); pp. 1075-1097. [cited by applicant]
Bisdom, Kevin et al.; “The impact of in-situ stress and outcrop-based fracture geometry on hydraulic aperture and upscaled permeability in fractured reservoirs” (abstract only) Tectonphysics v. 690, Part A, Oct. 28, 201… [cited by applicant]
Camargo, Otto E. Meza et al.; “Reservoir Stress Path from 4D Coupled High Resolution Geomechanics Model: A Case Study for Jauf Formation, North Ghawar, Saudi Arabia” Saudi Aramco Journal of Technology, Fall 2016; pp. 45… [cited by applicant]
Cao, Yang-Bing et al.; “Calculation Method and Distribution Characteristics of Fracture Hydraulic Aperture from Field Experiments in Fractured Granite Area” (abstract only), Springer Ling, Nov. 9, 2015; pp. 1-18. [cited by applicant]
Cappa, F. et al.; “Estimation of fracture flow parameters through numerical analysis of hydromechanical pressure pulses” Water Resources Research, American Geophysical Union, 2008, 44, pp. W11408; pp. 1-49. [cited by applicant]
Chen, Sheng et al.; “Prediction of sweet spots in shale reservoir based on geophysical well logging and 3D seismic data” Energy Exploration & Exploitation, vol. 35(2), 2017; pp. 147-171. [cited by applicant]
Engelder, Terry et al.; “Chapter 15: A Pore-Pressure Limit in Overpressured South Texas Oil and Gas Fields” pp. 255-267, AAPG Memoir 67, 1997; pp. 255-267. [cited by applicant]
Fischer, K. et al.; “A workflow for building and calibrating 3-D geomechoanical models—a case study for a gas reservoir in the North German Basin” Solid Earth, 4, (2013); pp. 347-355. [cited by applicant]
Gan, Quan et al.; “A continuum model for coupled stress and fluid flow in discrete fracture networks” Geomech. Geophys. Geo-energ. Geo-resour. (2016); pp. 2:43-61. [cited by applicant]
Gray, F. David et al.; “Fracture detection in the Manderson Field: A 3D AVAZ case history” Society of Exploration Geophysicists, Jan. 5, 2005; pp. 1-4. [cited by applicant]
Herwanger, J., Seismic Geomechanics, How to Build and Calibrate Geomechanical Models using 3D and 4D Seismic Data, 1 Edn., EAGE Publications b.v. Houten, 2011; Chapter 2, pp. 19-39, Chapter 6, pp. 102-118. [cited by applicant]
International Search Report and Written Opinion for International Application No. PCT/US2018/046824 (SA5707) report mail date Nov. 28, 2018; pp. 1-13. [cited by applicant]
International Search Report and Written Opinion for International Application No. PCT/US2020/062069 (SA51044), report mail date Mar. 11, 2021; pp. 1-18. [cited by applicant]
International Search Report and Written Opinion for International Application No. PCT/US2021/018379 (SA51284) report mail date May 28, 2021; pp. 1-16. [cited by applicant]
Jorgensen, Bo Barker et al.; “Bacterial Sulfate Reduction Above 100C in Deep-Sea Hydrothermal Vent Sediments” (Abstract only) Science, vol. 258, Issue 5089, Dec. 11, 1992; pp. 1756-1757. [cited by applicant]
Khadivi, Kourosh et al.; “Integrated fracture characterization of Asmari reservoir in Haftkel field” Journal of Petroleum Exploration and Production Technology, Jan. 4, 2022; pp. 1-21. [cited by applicant]
Koutsabeloulis, N.C. et al.; “Numerical geomechanics in reservoir engineering” Computer Methods and Advances in Geomechanics, A.A. Balkema, Rotterdam, The Netherlands, 1994; pp. 2097-2104. [cited by applicant]
Lei, Qinghua et al.; “The use of discrete fracture networks for modelling coupled geomechanical and hydrological behaviour of fracture rocks” Computers and Geotechnics 85 (2017); pp. 151-176. [cited by applicant]
Liu, Naizhen et al.; “Shale gas sweet spot identification and precise geo-steering drilling in Weiyuan Block of Sichuan Basin, SW China” Petroleum Exploration and Development, vol. 43, Issue 6, Dec. 2016; pp. 1-9. [cited by applicant]
Luthi, S.M. et al.; “Fracture apertures from electrical borehole scans” Geophysics, vol. 55, No. 7 (Jul. 1990); pp. 821-833. [cited by applicant]
Maerten, F.; “Adaptive cross-approximation applied to the solution of system of equations and post-Processing for 3D elastostatic problems using the boundary element Method” Engineering Analysis with Boundary Elements 3… [cited by applicant]
Matyasik, Irena et al.; “Genesis of hydrogen sulfide in carbonate reservoirs” Nafta-Gaz, Rok LXXIV, Nr Sep. 2018; pp. 627-635. [cited by applicant]
Min, Ki-Bok et al.; “Stress-Dependent Permeability of Fractured Rock Masses: A Numerical Study” International Journal of Rock Mechanics and Mining Sciences, vol. 41, Issue 7 (2004); pp. 1191-1210. [cited by applicant]
Nejadi, Siavash et al.; “History matching and uncertainty quantification of discrete fracture network models in fractured reservoirs” Journal of Petroleum Science and Engineering 152 (2017); pp. 21-32. [cited by applicant]
Orr, Wilson L.; “Changes in Sulfur Content and Isotopic Ratios of Sulfur during Petroleum Maturation—Study of Big Horn Basin Paleozoic Oils” The American Association of Petroleum Geologists Bulletin, V. 58, No. 11 (Nov.… [cited by applicant]
Rogers S. et al, “Integrating discrete fracture network models and pressure transient data for testing conceptual fracture models of the Valhall chalk reservoir, Norway North Sea”; Geological Society, London, Special Pu… [cited by applicant]
Rogers, Stephen F.; “Critical stress-related permeability in fractured rocks”, Chpt 2, Fracture and In-Situ Stress Characterization of Hydrocarbon Reservoirs, (AMEEN) Geoscience World, The Geological Society of London, … [cited by applicant]
Schlumberger; “Welcome to Techlog online help Feb. 2018” 2018; pp. 1-2. [cited by applicant]
Silverman, B.W.; “Density Estimation For Statistics and Data Analysis” Monographs on Statistics and Applied Probability, London: Chapman and Hall, 1986; pp. 1-22. [cited by applicant]
Sorkhabi, Rasoul, Ph.D.; “Locating Sweet Spots: Shale Petroleum Systems” available as of Dec. 28, 2021 at: https://www.geoexpro.com/articles/2020/06/locating-sweet-spots-shale-petroleum-systems; vol. 17, No. 2—2020; pp.… [cited by applicant]
Tokhmchi, Behzad et al.; “Estimation of the fracture density in fractured zones using petrophysical logs” Journal of Petroleum Science and Engineering 72 (2010); pp. 206-213. [cited by applicant]
U.S. Appl. No. 17/463,153 (SA51648) titled “Determining Hydrogen Sulfide (H2S) Concentration and Distribution in Carbonate Reservoirs Using Geomechanical Properties” filed Aug. 31, 2021. [cited by applicant]
U.S. Appl. No. 17/476,914 (SA51643) titled “Identifying Fluid Flow Paths in Naturally Fractured Reservoirs” filed Sep. 16, 2021. [cited by applicant]
U.S. Appl. No. 17/690,484 (SA51689) titled “Geo-Mechanical Based Determination of Sweet Spot Intervals for Hydraulic Fracturing Stimulation” filed Mar. 9, 2022. [cited by applicant]
Wikipedia; “Kernel density estimation” available as of Apr. 4, 22 at: https://en.wikipedia.org/wiki/Kernel_density_estimation#:˜:text=In statistics%2C kernel density estimation,on a finite data sample; pp. 1-12. [cited by applicant]
Worden, R.H. et al.; “Gas Souring by Thermochemical Sulfate Reduction by 140C1” The American Association of Petroleum Geologists Bulletin, V. 79, No. 6 (Jun. 1995); pp. 854-863. [cited by applicant]
Worden, Richard H. et al.; “Origin of H2S in Khuff Reservoirs by Thermochanical Sulfate Reduction: Evidence from Fluid Inclusions” Saudi Aramco Journal of Technology, Fall 2004; pp. 42-52. [cited by applicant]
Zellou, Abdel et al.; “Fractured Reservoir Characterization Using Post-Stack Seismic Attributes: Application to a Hungarian Reservoir”, EAGE 68th Conference & Exhibition—Vienna, Austria, Jun. 12-15, 2006; pp. 1-4. [cited by applicant]
Zhu, GuangYou et al.; “The controlling factors and distribution prediction of H2S formation in marine carbonate gas reservoir, China” (abstract only) Chinese Science Bulletin, vol. 52 (2007), pp. 150-163. [cited by applicant]
Zoback, Mark D.; “Chapter 11: Critically stressed faults and fluid flow” Reservoir Geomechanics, Cambridge University Press, New York, 2007, pp. 1-21. [cited by applicant]
Ge, Jun et al.; “Semianalytical modeling on 3D stress redistribution during hydraulic fracturing stimulation and its effects on natural fracture reactivation” Int J Numer Anal Methods Geomech. (2020) / V. 44, / 8; pp. 1… [cited by applicant]
Huang, Jian et al.; “Natural-hydraulic fracture interaction: Microseismic observations and geomechanical predictions” (abstract only) Interpretation (2015) 3 (3); pp. SU17-SU31. [cited by applicant]
Kayode, B. et al.; “Advances in Reservoir Modeling: A New Approach for Building Robust Reservoir Models” (abstract only) SPE-187993-MS, SPE KSA Annual Technical Symposium and Exhibition, Dammam, Saudi Arabia, Apr. 2017;… [cited by applicant]
Meza, O. et al.; “Integration of Borehole Image Logs and Rock Mechanics for Critically Stressed Fractures Analysis in Weak Carbonates” (abstract only) 2nd EAGE Borehole Geology Workshop, Oct. 2017, vol. 2017; pp. 1-5. [cited by applicant]
Ochie, Karen Ifeoma et al.; “Geostatistics—Kriging and Co-Kriging Methods in Reservoir Characterization of Hydrocarbon Rock Deposits” SPE-193483-MS, Nigeria Annual International Conference & Exhibition, Lagos, Nigeria, … [cited by applicant]
Zeng, Qingdong et al.; “Numerical Simulation of Fluid-Solid Coupling in Fractured Porous Media with Discrete Fracture Model and Extended Finite Element Method” Computation (2015), 3; pp. 541-557. [cited by applicant]
Alcantara, Ricardo et al.; “A Dynamic Characterization Approach for a Complex Naturally Fractured Reservoir” International Petroleum Technology Conference, Beijing, China, Mar. 26-28, 2019; pp. 1-40. [cited by applicant]
ArcGIS; “How Line Density works” available as of Jan. 18, 2022 at: https://desktop.arcgis.com/en/arcmap/10.6/tools/spatial-analyst-toolbox/how-line-density-works.htm; pp. 1-3. [cited by applicant]
Jiang, Le et al.; “Simulation and Optimization of Dynamic Fracture Parameters for an Inverted Square Nine-Spot Well Pattern in Tight Fractured Oil Reservoirs” Hindawi, Geofluids, vol. 2020, Article ID 8883803; pp. 1-9. [cited by applicant]
Liu, Shiqi et al.; “Geological and Engineering Integrated Shale Gas Sweet Spots Evaluation Based on Fuzzy Comprehensive Evaluation Method: A Case Study of Z Shale Gas Field HB Block” Energies 2022, 15, 602, Jan. 14, 202… [cited by applicant]
Ouenes, Ahmed; “Stress Modeling ‘3-G’ Workflow Pinpoints Shale Sweet Spots” The American Oil & Gas Reporter, Jul. 2015; pp. 1-3. [cited by applicant]
U.S. Appl. No. 17/721,064 (SA51697) titled “Identifying Naturally Fractured Sweet Spots Using a Fracture Density Index (FDI)” filed Apr. 14, 2022. [cited by applicant]
Zoback, Mark D.; “Critically stressed faults and fluid flow” Reservoir Geomechanics Chapter 11; Cambridge University Press (2007); pp. 1-20. [cited by applicant]
Akhmetova, A.A. et al.; “Evaluation of the applicability mini-fracturing data to determine reservoir pressure and transmissibility (Russian).” OIJ 2018 (2018); pp. 90-94. [cited by applicant]
Azari, Mehdi et al.; “Determining the Formation Properties with Innovative Formation Integrity Test Designed Using a Wireline Straddle Packer, A Field Example” SPWLA 59th Annual Logging Symposium, Jun. 2-6, 2018; pp. 1-… [cited by applicant]
Blakely, Richard J.; “Potential Theory in Gravity and Magnetic Applications” Cambridge University Press, 1996; pp. 1-9. [cited by applicant]
Ferreira, Francisco J.F. et al.; “Enhancement of the total horizontal gradient of magnetic anomalies using the tilt angle” Geophysics vol. 78, No. 3 (May-Jun. 2013); pp. J33-J41. [cited by applicant]
Friedman, Jerome H.; “Greedy Function Approximation: A Gradient Boosting Machine” 1999 Reitz Lecture, The Annals of Statistics (2001), vol. 29, No. 5; pp. 1189-1232. [cited by applicant]
Gunn, P.J.; “Linear Transformations of Gravity and Magnetic Fields” Geophysical Prospecting vol. 23, Issue 2, Jun. 1974; pp. 300-312. [cited by applicant]
Han, Jiahang et al.; “Stress Field Change Due to Reservoir Depletion and Its Impact on Refrac Treatment Design and SRV in Unconventional Reservoirs” SPE-178496-MS/URTeC:2144941; Unconventional Resources Tech. Conf., Tex… [cited by applicant]
Jacquemyn, Carl et al.; “Mechanical stratigraphy and (paleo-) karstification of the Murge area (Apulia, southern Italy)” (abstract only) Geological Society, London, Special Publicationsvol. 370; pp. 169-186. [cited by applicant]
Miller, Hugh G. et al.; “Potential field tilt—a new concept for location of potential field sources” Journal of Applied Geophysics 32 (1994); pp. 213-217. [cited by applicant]
Mojeddifar, Saeed et al.; “Porosity prediction from seismic inversion of a similarity attribute based on a pseudo-forward equation (PFE): a case study from the North Sea Basin, Netherlands” Pet. Sci. (2015) 12; pp. 428-… [cited by applicant]
Nolte, K.G. et al.; “After-Closure Analysis of Fracture Calibration Tests” SPE 38676, 1997 SPE Annual Technical Conference and Exhibition, San Antonio, TX, Oct. 5-8, 1997; pp. 333-349. [cited by applicant]
Phillips, Jeffrey D.; “Designing matched bandpass and azimuthal filters for the separation of potential-field anomalies by source region and source type” ASEG 15th Geophysical Conference and Exhibition, Aug. 2001, Brisb… [cited by applicant]
Rezmer-Cooper, Iain M. et al.; “Real-Time Formation Integrity Tests Using Downhole Data” IADC/SPE 59123, 2000 IASC/SPE Drilling Conference, New Orleans, LA, Feb. 23-25, 2000; pp. 1-12. [cited by applicant]
Schultz, Ryan et al.; “The Cardston Earthquake Swarm and Hydraulic Fracturing of the Exshaw Formation (Alberta Bakken Play)” Bulletin of the Seismological Society of America, vol. 105, No. 6, Dec. 2015; pp. 1-14. [cited by applicant]
Spector, A. et al.; “Statistical Models for Interpreting Aeromagnetic Data” Geophysics, vol. 35, No. 2, Apr. 1970; pp. 293-302. [cited by applicant]
Tian, Fei et al.; “Three-Dimensional Geophysical Characterization of Deeply Buried Paleokarst System in the Tahe Oilfield, Tarim Basin, China” Water (2019) 11, 1045; pp. 1-18. [cited by applicant]
Van Lanen, Xavier et al.; “Integrated geologic and geophysical studies of North American continental intraplate seismicity” The Geological Society of America, Special Paper 425, 2007; pp. 101-112. [cited by applicant]
Wilson, Adam; “Common Mistakes Associated with Diagnostic Fracture Injection Tests” Journal of Petroleum Technology, Aug. 31, 2014; pp. 1-6. [cited by applicant]
Wynants-Morel, Nicolas et al.; “Stress Perturbation From Aseismic Slip Drives the Seismic Front During Fluid Injection in a Permeable Fault” JGR Solid Earth vol. 125, Issue 7, Jul. 2020; pp. 1-23. [cited by applicant]
Barree, R.D. et al.; “Holistic Fracture Diagnostics” SPE 107877, Rocky Mountain Oil & Gas Technology Symposium, Denver, CO, Apr. 16-18, 2007; pp. 1-13. [cited by applicant]
Palamakumbura, Romesh et al.; “A review and evaluation of the methodology for digitising 2D fracture networks and topographic lineaments in GIS” Solid Earth Discussions; Preprint. Discussion started: Dec. 10, 2019; pp. … [cited by applicant]
Zhang, Jing et al.; “Statistical analysis of geological factors controlling bed-bounded fracture density in heterolithic shale reservoirs: The example of the Woodford Shale Formation (OK, USA)” J. of Petroleum Science &… [cited by applicant]