Surface Drilling Data for Constrained Hydraulic Fracturing and Fast Reservoir Simulation of Unconventional Wells

The objective is to present a new integrated workflow which leverages commonly available drilling data from multiple wells to build reservoir models to be used for designing and optimizing hydraulic fracture treatment and reservoir simulation. The use of surface drilling data provides valuable information along every wellbore. This information includes estimations of geomechanical logs, pore pressure, stresses, porosity and natural fractures. These rock properties may be used as a first approximation in a well-centric approach to geoengineer completions. Combining these logs from multiple wells into 3D reservoir models provides more value including using them in reservoir geomechanics, 3D planar hydraulic fracturing design and reservoir simulation. When using these 3D models and their results in a fast marching method simulator, the impact of the interference between wells can be estimated quickly while providing results like those derived with a classical reservoir simulator. Integrating surface drilling data with 3D reservoir models, hydraulic fracturing design and reservoir simulation into a single software platform results in a fast and constrained approach which allows for a more efficient management of unconventional wells

Neural networks in petroleum geology as interpretation tools

Abstract Three examples of the use of neural networks in analyses of geologic data from hydrocarbon reservoirs are presented. All networks are trained with data originating from clastic reservoirs of Neogene age located in the Croatian part of the Pannonian Basin. Training always included similar reservoir variables, i.e. electric logs (resistivity, spontaneous potential) and lithology determined from cores or logs and described as sandstone or marl, with categorical values in intervals. Selected variables also include hydrocarbon saturation, also represented by a categorical variable, average reservoir porosity calculated from interpreted well logs, and seismic attributes. In all three neural models some of the mentioned inputs were used for analyzing data collected from three different oil fields in the Croatian part of the Pannonian Basin. It is shown that selection of geologically and physically linked variables play a key role in the process of network training, validating and processing. The aim of this study was to establish relationships between log-derived data, core data, and seismic attributes. Three case studies are described in this paper to illustrate the use of neural network prediction of sandstone-marl facies (Case Study # 1, Okoli Field), prediction of carbonate breccia porosity (Case Study # 2, Beničanci Field), and prediction of lithology and saturation (Case Study # 3, Kloštar Field). The results of these studies indicate that this method is capable of providing better understanding of some clastic Neogene reservoirs in the Croatian part of the Pannonian Basin

Integration of Advanced Geoscience and Engineering Techniques to Quantify Interwell Heterogeneity. Quarterly Technical Report, January 1, 1996--March 31, 1996

The objective of this project is to integrate advanced geoscience and reservoir engineering concepts with the goal of quantifying the dynamics of fluid-rock and fluid-fluid interactions as they relate to reservoir architecture and lithologic characterization. This interdisciplinary effort will integrate geological and geophysical data with engineering and petrophysical results through reservoir simulation. The essence of the work completed in the first quarter of 1996 is summarized in the following three statements: automatic log digitizing software is superior to hand digitizing; laboratory wettability tests suggest that the reservoir is mixed-wet and results of the non-reactive tracer test were used to revise the mechanics of the wettability test design to include tracer injection below a packer

Integration of Advanced Geoscience and Engineering Techniques to Quantify Interwell Heterogeneity. Quarterly Technical Report, April 1, 1996--June 30, 1996

The objective of this project is to integrate advanced geoscience and reservoir engineering concepts with the goal of quantifying the dynamics of fluid-rock and fluid-fluid interactions as they relate reservoir architecture and lithologic characterization. This interdisciplinary effort will integrate geological and geophysical data with engineering and petrophysical results through reservoir simulation. Subcontractors from Stanford University and the University of Texas at Austin are collaborating on the project. Several members of the Petroleum Recovery Research Center are participating in the development of the improved reservoir description by integration of the field and laboratory data, as well as in the development of quantitative reservoir models to aid performance predictions. Technical progress is summarized for geologic studies and field operations at Sulimar Queen Field, New Mexico, and technology transfer from this study

Integration of advanced geoscience and engineering techniques to quantify interwell heterogeneity. Quarterly technical report, July 1, 1995--September 30, 1995

The objective of this project is to integrate advanced geoscience and reservoir engineering concepts with the goal of quantifying the dynamics of fluid-rock and fluid-fluid interactions as they relate to reservoir architecture and lithologic characterization. This interdisciplinary effort will integrate geological and geophysical data with engineering and petrophysical results through reservoir simulation. Several members of the PPRC staff are participating in the development of improved reservoir description by integration of the field and laboratory data, as well as in the development of quantitative reservoir models to aid performance predictions

Integration of advanced geoscience and engineering techniques to quantify interwell heterogeneity. Quarterly report, 1 October 1995--31 December 1995

The objective of this project is to integrate advanced geoscience and reservoir engineering concepts with the goal of quantifying the dynamics of fluid-rock and fluid-fluid interactions as they relate to reservoir architecture and lithologic characterization. This interdisciplinary effort will integrate geological and geophysical data with engineering and petrophysical results through reservoir simulation. Technical progress is reported for: Geologic studies, single well wettability tracer test for Sulimar Queen Field; field operations; and reservoir modeling

Integration of advanced geoscience and engineering techniques to quantify interwell heterogeneity in reservoir models. Final report, September 29, 1993--September 30, 1996

The goal of this three-year project was to provide a quantitative definition of reservoir heterogeneity. This objective was accomplished through the integration of geologic, geophysical, and engineering databases into a multi-disciplinary understanding of reservoir architecture and associated fluid-rock and fluid-fluid interactions. This interdisciplinary effort integrated geological and geophysical data with engineering and petrophysical results through reservoir simulation to quantify reservoir architecture and the dynamics of fluid-rock and fluid-fluid interactions. An improved reservoir description allows greater accuracy and confidence during simulation and modeling as steps toward gaining greater recovery efficiency from existing reservoirs. A field laboratory, the Sulimar Queen Unit, was available for the field research. Several members of the PRRC staff participated in the development of improved reservoir description by integration of the field and laboratory data as well as in the development of quantitative reservoir models to aid performance predictions. Subcontractors from Stanford University and the University of Texas at Austin (UT) collaborated in the research and participated in the design and interpretation of field tests. The three-year project was initiated in September 1993 and led to the development and application of various reservoir description methodologies. A new approach for visualizing production data graphically was developed and implemented on the Internet. Using production data and old gamma rays logs, a black oil reservoir model that honors both primary and secondary performance was developed. The old gamma ray logs were used after applying a resealing technique, which was crucial for the success of the project. In addition to the gamma ray logs, the development of the reservoir model benefitted from an inverse Drill Stem Test (DST) technique which provided initial estimates of the reservoir permeability at different wells

Reservoir management applications to oil reservoirs

Winnipegosis and Red River oil production in the Bainville North Field in Roosevelt County, Montana began in 1979. The Red River is at 12,500 ft and one well is completed in the Nisku formation at 10,200 ft. This well produced 125,000 bbl from the Nisku during its first 41 months. Since operating conditions inhibit dual completions and Nisku wells cost $900,000, the need for a Nisku development plan is apparent. The size of the reservoir and optimum well density are the key unknowns. Recognizing the need for additional Nisku data, a 5000 acre 3-D seismic survey was processed and the results used to map the top of the Nisku. The reservoir thickness, porosity, and water saturation were known from the openhole logs at eight well locations on an average of 320 acres spacing. The thickness of the thin pay limited the seismic information to areal extent of reservoir depth. Static reservoir pressure from drillstem test was available at two wells. Additional reservoir pressure data in the form of transient tests were available at two wells. Under Los Alamos National Laboratory Basic Ordering Agreement 9-XU3-0402J-1, the New Mexico Petroleum Recovery Research Center (PRRC) characterized the Nisku to develop a reservoir management plan. Nance Petroleum provided all available field and laboratory data for characterizing the Nisku formation. Due to sparse well coverage, and the lack of producing wells, the PRRC had to develop a new reservoir description approach to reach an acceptable characterization of the entire reservoir. This new approach relies on the simultaneous use of 3-D seismic and reservoir simulation to estimate key reservoir properties