Engineering Creativity Award:  Innovative Hydrocarbon       Production Systems Using Nodal Systems Analysis and Expert  Systems
{'Code': '07050000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'EEC', 'LongName': 'Div Of Engineering Education and Centers'}}
{'SignBlockName': 'Sue Kemnitzer', 'PO_EMAI': None, 'PO_PHON': None}
A relatively new method of optimizing the production of                         hydrocarbon wells is Nodal System Analysis (NSA) which integrates               the multiple pressure differentials occurring in the transfer of                hydrocarbon fluid from the reservoir to the surface.  The                       objective of the research is to expand NSA and to investigate the               design of a Expert System Production Organizer (ESPO) using a                   rule-based system.  This ESPO well consist of a package of                      interactive software employing NSA technology.  The programmed                  expert system will analyze the complexities of a production well                in a single package and can be accessed by engineers with little                or no knowledge of NSA.                                                         The ESPO will possess these features: (1) all flow correlations                 and models are internal, (2) frequently-used data is available in               on-line databases accessed internally by software, (3) an                       economics package that compares selected production schemes, (4)                perform statistical analysis on similar wells, (5) an inference                 engine for forward and backward chaining, (6) analyze the                       production systems and identify possible solutions, and (7) be                  user friendly.
{'FirstName': 'Khalid', 'LastName': 'Aziz', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Khalid Aziz', 'EmailAddress': 'aziz@stanford.edu', 'NSF_ID': '000326406', 'StartDate': '09/01/1988', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'Stanford University', 'CityName': 'STANFORD', 'ZipCode': '943052004', 'PhoneNumber': '6507232300', 'StreetAddress': '450 JANE STANFORD WAY', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '16', 'CONGRESS_DISTRICT_ORG': 'CA16', 'ORG_UEI_NUM': 'HJD6G4D6TJY5', 'ORG_LGL_BUS_NAME': 'THE LELAND STANFORD JUNIOR UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
{'Name': None, 'CityName': None, 'StateCode': None, 'ZipCode': None, 'StreetAddress': None, 'CountryCode': None, 'CountryName': None, 'StateName': None, 'CountryFlag': None, 'CONGRESSDISTRICT': None, 'CONGRESS_DISTRICT_PERF': '""'}
{'Code': '1360', 'Text': 'EWFD-Eng Workforce Development'}
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1988&All=true', 'xml': '8811643.xml'}