New technology makes impact on old East Texas water flood

Zone Energy LLC is a small, investor-backed start-up operator focused on US-based brownfield acquisitions, drilling, recovery optimization including EOR, and divestitures. The company acquired producing assets and open leases in the giant East Texas field in Greg and Rusk counties. Zone implements water injection and the application of state-of-the-art methods and technologies to improve producing assets. While production increases are critical to their success, the company employs an “automate and optimize” strategy to drive down personnel and operational costs.

The East Texas field was discovered in 1930 and has produced more than 5 Bbbl of oil to date. It still supports more than 100 operators today who cumulatively generate more than 10,000 b/d of oil production. The field produces primarily from fluvio-deltaic reservoirs of Cretaceous age of the Woodbine formation. Zone Energy operates a patterned waterflood program of approximately 100 producing and 17 injecting wells. Early technical work concentrated on developing a sequence stratigraphic framework, reservoir characterization, production forecasting, and reserve estimation, all of which were supported by Petra and PHDWin.

Initial challenge

Zone acquired the initial package of assets in June 2010. As part of the acquisition, the company received very little in the way of any organized production database or field data capture system. To support reservoir, production, and operational analysis, the company employed Microsoft Excel as the short-term mechanism to manage fundamental technical and operational requirements. This strategy – although workable in the short term – left significant remaining challenges as the operational footprint grew in size. Challenges included:

• A rapidly growing list of Excel files with inherent data management and quality control challenges;
• Minimal automation within existing processes;
• Manual data quality control and inconsistent field data collection;
• Manual allocations and nonquantifiable downtime as a component of the allocations;
• Manual tracking of water injection efficiency or optimization; and
• Limited access of data across the multidisciplinary team and management.

FIGURE 1. The well review tool used by Zone Energy provides live summaries of data tied to selected wells. (Images courtesy of Zone Energy and OVS Group)

Improvement plan

Zone felt it could leverage commercial technology to resolve a significant portion of the existing challenges. The bigger question was related to the cost and timing. To address this issue, Zone selected OVS Group’s production optimization framework and associated engineering services. OVS and Zone worked together to capture an appropriate implementation design based on the existing data sources, Zone’s third-party tools, and the engineering workflows Zone required. As part of the solution, Zone wanted to create workflows that could take advantage of the tools it already uses and expand its ability to support the following:

• Move away from Excel as its comprehensive database and analytical/reporting tool yet provide the ability to easily export data to Microsoft Office products;
• Create a secure production and operational database (SQL Server) where the bulk of the Excel data could reside and that could scale with expansion and provide secure data hosting;
• Capture well tests with an improved quality control capability, generate consistent downtime reports, and support other field measurements and reports;
• Automate, within practical limits, the surveillance of daily measurements and events using an “unattended” approach where the field foreman is notified by email if something requires investigation or notification;
• Improve allocations to include all downtime reports with more flexible, individual well-weighting capabilities;
• Support a browser-like “well review tool” that would allow all aspects of each well to be integrated to a single dashboard for rapid investigation regardless of data source;
• In the same dashboard, support all lease and polygon information with map and table-based presentations and all tanks and meters. All data should be refreshed automatically to the dashboard based on surveillance methods or unattended scheduling;
• Support analytics surrounding reservoir heterogeneity plots and voidage replacement ratio plots; and
• Provide an extendible final design for future expansion of workflows into regulatory reporting, reservoir analysis, and reserves tracking (with lease ownership, working, revenue and royalty interest, and acreage already captured).

Results

Implementation of the solution enabled the company to migrate from spreadsheets for its production and operational data to an OVS-delivered fit-for-purpose SQL Server database and transfer the bulk of the Excel data into the repository. The OVS framework also provides the functionality to connect to other third-party database repositories. This functionality allows the OVS functionality to run directly from third-party database connections.

The OVS framework was employed to quality-control the transfer of the existing data as the first step in the process. In the short term the field organization continued to enter field data into Excel, and workflows were created that automatically picked up the Excel files, extracted the key data following a quality-control check, and then loaded the data into the database for further analytics and reports.

The company subsequently implemented a third-party drilling reporting and wellbore schematic tool that OVS connected to for integration to the well review tool in the Zone framework.

With well tests now being checked for quality and stored, a well back-allocation calculation was implemented, driven by the well test results and weighted by well performance according to Zone’s interpretation. The system automatically locks down the allocations based on the date and reporting requirements. The dashboard was implemented based on the entities that Zone required (Figure 1).

Downtime is now reported as time and production losses, calculated through the well back-allocation system. In addition, specific reports are generated to capture the type of downtime for more complete production reporting.

FIGURE 2. Using the pattern analysis window, engineers are able to investigate production by pattern (which includes the associated wells). In this case a particular pattern is selected, and the resulting cross-plots summarize the voidage replacement ratio, oil production, and water production of the pattern.

Dynamic reports of the various entities being tracked are presented by the system: producing and injection wells, patterns, projects, tanks, meters, equipment, and daily field-data capture. The live reports are context-sensitive and update as an entity is selected.

Zone now relies on the system to automatically report data for submission to the Texas Railroad Commission. The company also migrated successfully from Excel-based pattern analysis to dynamic pattern analysis reports calculated and presented by the system (Figure 2).

Next steps, successes

Zone was successful in achieving a significant improvement in field operations and analytical efficiency by establishing impactful workflows through the OVS system. The system has been fully embraced by senior executives, engineers, and field operators. Data quality control and operational transparency have improved dramatically along with data security, scalability, and automation. Zone was able to implement the improvements, including the software, relying on a budget similar in cost to one man-year of a junior engineer. Zone will next expand its surveillance methodology to better predict operational conditions that lead to production losses.