A Practical Approach to History Matching Premature Water Breakthrough in Waterflood Reservoir Simulation: Method and Case Studies in South Belridge Diatomite Waterflood

Yang, Zhengming; Urdaneta, Alfredo

doi:10.2118/174006-pa

Cited by 5 publications

(1 citation statement)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Before water breakthrough, there is a period of nearly flat Y-function trend whose length depends on the initial and irreducible water saturation. A significant abnormality from the type curve indicates a possible premature water breakthrough issue (Yang, 2016). Recompletion and/or reconfiguration is another aspect.…”

Section: From 1-d Model To 3-d Field Applicationmentioning

confidence: 99%

Clarifying and Improving the Application of Waterflood Analytical Methods in X-Plot Conditions – From Empirical Approach to Analytical Approach

Yang¹

2017

SPE Western Regional Meeting

Self Cite

View full text Add to dashboard Cite

X-plot method is the waterflood analysis method derived from 1-D Buckley-Leverett equation (Ershaghi and Omoregie, 1978) based on a semi-log relationship between oil/water relative permeability ratio and water saturation. X-plot method (Q o =mX+n) is a linear relationship between cumulative oil (Q o ) and a water-cut feature variable X=ln(1/f w -1)-1/f w . Using an empirical approach, the slope m and intercept n are determined by linear-regression of historical production data and then extrapolated to a higher water-cut to predict recoverable oil. The limitations to field application include: 1) post-breakthrough waterflood period; 2) unfavorable mobility ratio in 3-D field condition; and 3) major pattern reconfiguration events such as infill-drilling and perforation interval addition may impact parameters m and n. Clarifying those limitations and their impact will minimize uncertainty and bias in the practical application.X-plot condition is defined as the water saturation range or recovery period when the X-plot method applies which is from water breakthrough to an economically feasible higher water-cut. The objective of this paper is to clarify and improve the application of waterflood analytical methods in X-plot conditions. Various analytical methods have been developed and their internal relation with the X-plot method in field condition are clarified. An analytical approach is proposed, where the X-plot method slope m and intercept n are determined by diagnosing production performance rather than by empirical regression. With parameters m and n determined analytically, the X-plot method is applied to forecast recoverable oil. The 1-D model case and field case studies compare the X-plot method in analytical and empirical approaches. The case studies indicate that with only minimal post-breakthrough waterflood production data the analytical approach for X-plot method will reduce uncertainty and bias in the long-term recoverable oil prediction.

show abstract

Section: From 1-d Model To 3-d Field Applicationmentioning

confidence: 99%

Clarifying and Improving the Application of Waterflood Analytical Methods in X-Plot Conditions – From Empirical Approach to Analytical Approach

Yang¹

2017

SPE Western Regional Meeting

Self Cite

View full text Add to dashboard Cite

show abstract

Learning Reservoir Dynamics Metrics of Improved Oil Recovery Projects by Harnessing Real-Time Analysis and Data Analytics

Bustamante

Kabir

Reza

2018

SPE Improved Oil Recovery Conference

View full text Add to dashboard Cite

Real-time analysis and data analytics have become cornerstones in reservoir management of waterflood operations or conformance program. Connectivity between injector-producer pairs and premature breakthrough of injected water or gas are perennial issues that can make or break the economics of secondary and tertiary recovery projects. In this study, we aim to harness the advances in modern data analytics and real-time analysis to systematically evaluate a suite of standard diagnostics tools and propose novel ones for improved recovery projects. Although the scope of these reservoir dynamics evaluation tools can be extensive, our current investigation utilizes data from the Permian Basin. A suite of reservoir models under varying conditions involving water injection helped understand and evaluate a number of diagnostics tools and devise new characteristics plots. We performed over 8,000 model runs and used data analytics to assess these tools. These tools include water/oil ratio (WOR) vs. time plot, Chan diagnostics, reciprocal-productivity index (RPI) plot, gas/oil ratio (GOR) vs. time plot, among others. We investigated the well-spacing effect ranging from 20 to 320 acres, grid effects, and heterogeneity effects in evaluating these tools. We also explored heterogeneity measures, such as the Dykstra-Parsons method and an index based on final hydrocarbon pore-volume injection (HCPVI), and ultimate recovery. Both cluster analysis and K-means statistics aided this screening process. This study illuminates initial-RPI (IRPI) that has a linear relationship with the ultimate recovery. Cluster analysis of the spread and uncertainty in final recovery vs. IRPI reveals scale invariance. In other words, this diagnostic plot can correctly identify and cluster the spread in final recovery under various well and reservoir quality scenarios, irrespective of the well spacing. Comparison of the final RPI and that at breakthrough with those at initial conditions suggests that IRPI can be a relevant reservoir performance indicator. This study shows critical parameters for oil recovery under waterflooding are reservoir flow paths and connectivity between layers, reservoir storativity, fluid properties, the thickness of the oil/water transition zone, and fluid mobilities. We also observed that the water breakthrough time does not show a clear relationship with IRPI. Nonetheless, the HCPVI at breakthrough time exhibited a linear correlation with the ultimate oil recovery. In the absence of water production or the presence of water channeling a linear trend emerges for the final HCPVI plot. Cluster analysis and real-time production data analysis have demonstrated the strength of a new reservoir dynamics indicator plot of ultimate hydrocarbon recovery vs. initial reciprocal productivity index. Combination of this indicator and traditional diagnostics and heterogeneity index can quantify the spread of final recovery efficiently.

show abstract

Predicting and Applying Wellhead Temperatures for Steamflood-Field Operation and Production-Performance Monitoring

Yang¹

2020

SPE Reservoir Evaluation &Amp; Engineering

View full text Add to dashboard Cite

Summary Producer-flowline temperatures (FLTs) can be measured automatically with a thermistor on an emergency-shutdown system (ESD), or manually on a specified spot on flowline with a handheld unit. Measured FLTs can usually be mapped to represent the formation-temperature distribution for steamflood reservoir management purposes (Hong 1994; Nath et al. 2007). In addition to FLT, wellhead temperature (WHT) is another surface temperature. Predicting the long-term WHT trend in steamflood operation is necessary for designing surface facilities for both oil dehydration/separation and produced-water recycling. This predicted temperature will also be applicable for production-performance monitoring. To predict the wellhead temperature, Hasan et al. (2009) derived a steady-state analytical solution for calculating WHT from bottomhole temperature (BHT) under flowing conditions of a multisection slant wellbore for the isothermal primary-depletion process, with both WHT and BHT being time independent for a given gross rate (Igec et al. 2010). This steady-state analytical solution has been extended to calculate steamflood producer WHT from BHT (both are time dependent) by consecutively approximating the WHT and monthly average of FLT measurements to a steady-state solution. The monthly averaged FLTs are seasonally variable and higher in the summer months of July through September and lower in the winter months of December through February. Monthly averaged FLT measurements depend on an annual ambient-temperature cycle within the depth needed for reaching an undisturbed ground temperature (typically 30 to 50 ft) (Gwadera et al. 2017). WHT, if measured, should be comparable with FLT for their close typical distance of 5 to 10 ft. WHT prediction, however, is only process dependent and not seasonally variable because of the inability to describe seasonally undisturbed depth in the geothermal gradient. Therefore, WHT prediction can be validated with average summer-month FLT measurements when heat loss becomes minimal. BHTs in this analytical approach are predicted by the Lauwerier (1955) analytical model and improved by calibration with the available reservoir-simulation model or several years of FLT measurements for steamflood response time. The objective of this study is to develop an integrated production-monitoring approach using only the surface information, including WHT and FLT, oil/water-production rate, and injection-pressure/rate data, which can be applied to diagnose and optimize steamflood production performance. A field case study for the South Belridge Diatomite steamflood was investigated. WHT prediction is compared with FLT measurement for diagnosing and understanding the production performances, such as premature water or steam breakthrough, interference by the waterflood on the steamflood boundary producers, as well as the FLT variation related to the target rates for steam injection. This diagnostic analysis approach combined with the Buckley-Leverett theory-based displacement-efficiency analysis, and injection pressure and rate signal, will help to develop an improved understanding of the displacement detail and form a decision base to optimize the production performance.

show abstract

A Practical Approach to History Matching Premature Water Breakthrough in Waterflood Reservoir Simulation: Method and Case Studies in South Belridge Diatomite Waterflood

Cited by 5 publications

References 8 publications

Clarifying and Improving the Application of Waterflood Analytical Methods in X-Plot Conditions – From Empirical Approach to Analytical Approach

Clarifying and Improving the Application of Waterflood Analytical Methods in X-Plot Conditions – From Empirical Approach to Analytical Approach

Learning Reservoir Dynamics Metrics of Improved Oil Recovery Projects by Harnessing Real-Time Analysis and Data Analytics

Predicting and Applying Wellhead Temperatures for Steamflood-Field Operation and Production-Performance Monitoring

Contact Info

Product

Resources

About