EnSys Yocum
Providing Software and Services for Oil Field Performance Improvement

Phone: (781) 274-8454 | Email: info@ensysyocum.net | Downstream contact: martin@tallett.co

Oil Field Insights

Using EnSys Yocum WELLSIM to Rapidly Estimate Oil Reservoir Attributes

“If you can get 80% of the accuracy at 20% of the cost, it is worth it 100% of the time.” We find this to be an especially fitting statement with respect to the ability of the EnSys Yocum Black Oil Model to back-calculate often “expensive to determine downhole information” from already known information. The Black Oil Model is truly an integrated tool which can employ a known set of oil well data to determine other well data. In essence, the Model has certain flexibilities with respect to the data that the user wishes to calculate. For example, the Black Oil Model conventionally uses reservoir data, coupled with well configuration data (i.e. well depth, casing diameter, etc.), to determine multiphase flow rates. However, in several past instances, EnSys Yocum has actually used test separator information, supported by well configuration data, to calculate the productivity index (PI) from the static and flowing bottomhole pressures for a given liquid flow rate. The static reservoir pressure (PSO) is calculated separately by a simulation run performed at a very low well flow rate.

Why would an operator want to estimate reservoir info? This information can be synthesized with other data to improve oil field performance and maximize oil production. However, conducting wireline tests are often labor and capital intensive processes. This is where the EnSys Yocum Black Oil Model comes in as it can compute reasonably accurate reservoir and flowing bottomhole pressure values in a matter of minutes —saving operators time and money. Additionally, these calculations can be made for each well in an entire field over a short amount of time which stands in contrast to downhole wireline tests which may only be conducted for a select number of wells due to time and cost. The following paragraphs detail further analysis with respect to downhole well data and historical applications of back-calculations, including one involving gas-lift wells.

Further Discussion regarding Downhole Well Data
A significant fraction of the pressure drop between the static reservoir pressure and the wellhead pressure typically occurs across the reservoir pay. The fraction of total pressure drop occurring in the reservoir pay generally depends on the well configuration, total liquid flow rate and the reservoir productivity index (PI). Therefore, in varying degrees, properly estimating the (PI) is key to accurately simulating production systems extending from the reservoir pay zone to the terminus. An accurate determination of the bottomhole pressure and temperature to provide an accurate (PI) estimate is particularly important where there is extended reservoir contact and/or a significant lack of reservoir homogeneity.

Accurate prediction of multiphase flow rates using an accurate estimate of the (PI) provides the ability to monitor well performance, and to determine how natural flow wells and electric submersible pump and gas lift systems are performing, and to help allocate flow among wells with comingled production.

The penetration of downhole cabled monitoring systems remains relatively low and their application for intelligent well systems is limited, particularly where the well completion is discontinuous, for multi-lateral horizontal wells and for slim-hole or mono-bore completions. And while wireless technology has been installed selectively to monitor and transmit flowing bottomhole pressure (FHBP) on a continuous basis, widespread adoption is still limited.

Two examples are described below in which EnSys Yocum has successfully applied WELLSIM to predict the (PI). The first application is on a natural flow well in the Middle East that is produced from a fractured reservoir and is thus characterized by variable productivity with flow rate. The second case is for an offshore Indian gas lifted well. This well was characterized by slug and stratified flow regimes generated in horizontal well laterals, along with pulsating flow in the central reservoir water injection system. In both cases, available downhole data was relatively sparse.
For both of these applications, multiphase oil/water and gas flows were matched within 10 to 15 percent accuracy as compared to well test separator results, confirming the accurate representation of fluid physical properties data and description of the well configuration. By running WELLSIM in conjunction with well test separator results obtained at given points in time, the (PI) was back-calculated to reduce the need for more frequent bottomhole wireline tests to measure FHBP and the static reservoir pressure (PSO) required to calculate the productivity index.
The static reservoir pressure and temperature (along with water cut and non-associated free reservoir gas) were obtained from historical trendline analysis. Once these values were established and the accuracy of the predicted multiphase flow rates confirmed, the need for frequent bottomhole wireline tests is significantly reduced because WELLSIM can be easily employed. This methodology can be applied across a wide range of well types and reservoir characteristics.

Example 1: Middle East Natural Flow Well
This application was for a non-homogeneous fractured reservoir with an established productivity index of 9.5 corresponding to a total (oil + water) flow rate of 4,500 bpd. The static reservoir pressure was 4,400 psi and the reservoir temperature was 265 ˚F. At the 4,500 bpd total liquid flow rate, the pressure drop across the reservoir pay was 510 psi decreasing to a tubing head pressure of 680 psi at the top of an 8,950 ft. long 2.5 in. outside diameter producing tubing. The reservoir fluid summary properties were 40.6 API, 970 GOR with an additional non-associated (free) gas rate of 200 GOR flowing into the well from the reservoir. The water cut fraction had been measured at 0.38.

Multiphase flow rate predictions for the 9.5 productivity / 4,500 barrels per day total flow case were initially within 16 percent for the total gas produced and 11 percent for the oil and water flow rates. EnSys Yocum conducted an analysis of the WELLSIM well simulation results, comparing predicted multiphase flow rates against a number of wellhead test separator results spaced across time and independently conducted by two contractors. As anticipated given the reservoir formation characteristics and the relatively high flow rate of free gas, the analysis clearly established that the (PI) increased markedly with total well liquid flow rate.

The results of the analysis are shown below spanning a range from approximately 1.0 to 12 (PI) and a total well flow rate of from 1000 to 5000 bpd, where the PI was back calculated as described above. Applying the results of the analysis to the total population of well heads separator tests yielded an accuracy of predicted versus test separator results of 6 percent for the oil flow and 11 percent for the gas flow.

PI Function across 9 Test cases

Example 2: Gas Lifted Wells in Offshore India
EnSys Yocum implemented WELLSIM for an Indian offshore field to calculate multiphase flow rates. The platform wells were inclined and horizontal, producing with fluctuating, short and long transient well pressures and flow rates.

EnSys Yocum carried out extensive simulation for well flow studies with WELLSIM. Findings indicated that slug and stratified flow regimes were being generated in the horizontal well laterals, and pulsating flow in the central well injector waterflood, resulting in producing well pressure/ flow rate fluctuations (± 15%).
Offline gas injection well optimization studies were conducted to determine maximum oil production rate at minimum gas injection rate. Bottomhole data was sparse and WELLSIM calculations were performed to back calculate the flowing bottom-hole pressure and (PI) in conjunction with trendline analysis for static reservoir pressure, flowing bottomhole pressure, productivity index,, water cut fraction, and reservoir free gas flow.

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