{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/76569"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/76569","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Data quality enhancement in oil reservoir operations : an application of IPMAP","abstract":"This thesis presents a study of data quality enhancement opportunities in upstream oil and gas industry. Information Product MAP (IPMAP) methodology is used in reservoir pressure and reservoir simulation data, to propose data quality recommendations for the company under study. In particular, a new 4-step methodology for examining data quality for reservoir pressure management systems is proposed: 1. Trace the data flow and draw the IPMAP; 2. Highlight the cross-system and organizational boundaries; 3. Select data quality analytical questions based on data quality literature review; 4. Apply the analytical questions at each boundary and document the results. This original methodology is applied to the three management systems to collect a pressure survey: using a spreadsheet, a standardized database and an automated database. IPMAPs are drawn to each of these three systems and cross-system and organizational boundaries are highlighted. Next, data quality systematic questions are applied. As a result, three data quality problems are identified and documented: well identifier number, well bore data and reservoir datum. The second experiment investigates the data quality issues in the scope of reservoir simulation and forecasting. A high-level IPMAP and a process flow on reservoir simulation and forecasting are generated. The next section further elaborates on the first high level process flow and drills into the process flow for simulation. The analytical data quality questions are raised to the second simulation process flow and limited findings were documented. This thesis concludes with lessons learned and directions for future research.","abstract_html":"This thesis presents a study of data quality enhancement opportunities in upstream oil and gas industry. Information Product MAP (IPMAP) methodology is used in reservoir pressure and reservoir simulation data, to propose data quality recommendations for the company under study. In particular, a new 4-step methodology for examining data quality for reservoir pressure management systems is proposed: 1. Trace the data flow and draw the IPMAP; 2. Highlight the cross-system and organizational boundaries; 3. Select data quality analytical questions based on data quality literature review; 4. Apply the analytical questions at each boundary and document the results. This original methodology is applied to the three management systems to collect a pressure survey: using a spreadsheet, a standardized database and an automated database. IPMAPs are drawn to each of these three systems and cross-system and organizational boundaries are highlighted. Next, data quality systematic questions are applied. As a result, three data quality problems are identified and documented: well identifier number, well bore data and reservoir datum. The second experiment investigates the data quality issues in the scope of reservoir simulation and forecasting. A high-level IPMAP and a process flow on reservoir simulation and forecasting are generated. The next section further elaborates on the first high level process flow and drills into the process flow for simulation. The analytical data quality questions are raised to the second simulation process flow and limited findings were documented. This thesis concludes with lessons learned and directions for future research.","abstract_has_math":false,"creators":["Lin, Paul Hong-Yi"],"institution":"Massachusetts Institute of Technology","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. Engineering Systems Division.","school":null,"contributors":[],"advisors":["Stuart E Madnick."],"committee_chairs":[],"committee_members":[],"year":2012,"date_issued":"2012","date_published":"2012","updated_at":"2026-07-22T22:22:17Z","subjects":["Engineering Systems Division.","System Design and Management Program."],"languages":["eng"],"rights":["M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 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Information Product MAP (IPMAP) methodology is used in reservoir pressure and reservoir simulation data, to propose data quality recommendations for the company under study. In particular, a new 4-step methodology for examining data quality for reservoir pressure management systems is proposed: 1. Trace the data flow and draw the IPMAP; 2. Highlight the cross-system and organizational boundaries; 3. Select data quality analytical questions based on data quality literature review; 4. Apply the analytical questions at each boundary and document the results. This original methodology is applied to the three management systems to collect a pressure survey: using a spreadsheet, a standardized database and an automated database. IPMAPs are drawn to each of these three systems and cross-system and organizational boundaries are highlighted. Next, data quality systematic questions are applied. As a result, three data quality problems are identified and documented: well identifier number, well bore data and reservoir datum. The second experiment investigates the data quality issues in the scope of reservoir simulation and forecasting. A high-level IPMAP and a process flow on reservoir simulation and forecasting are generated. The next section further elaborates on the first high level process flow and drills into the process flow for simulation. The analytical data quality questions are raised to the second simulation process flow and limited findings were documented. 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