Stochastic Inversion for Reservoir Properties Using Time-lapse Seismic and Well Production Data

Author(s):  
P. Stoffa ◽  
L. Jin ◽  
M. Sen ◽  
R. Seif ◽  
A. Sena
2001 ◽  
Vol 41 (1) ◽  
pp. 679
Author(s):  
S. Reymond ◽  
E. Matthews ◽  
B. Sissons

This case study illustrates how 3D generalised inversion of seismic facies for reservoir parameters can be successfully applied to image and laterally predict reservoir parameters in laterally discontinuous turbiditic depositional environment where hydrocarbon pools are located in complex combined stratigraphic-structural traps. Such conditions mean that structural mapping is inadequate to define traps and to estimate reserves in place. Conventional seismic amplitude analysis has been used to aid definition but was not sufficient to guarantee presence of economic hydrocarbons in potential reservoir pools. The Ngatoro Field in Taranaki, New Zealand has been producing for nine years. Currently the field is producing 1,000 bopd from seven wells and at three surface locations down from a peak of over 1,500 bopd. The field production stations have been analysed using new techniques in 3D seismic imaging to locate bypassed oils and identify undrained pools. To define the objectives of the study, three questions were asked:Can we image reservoir pools in a complex stratigraphic and structural environment where conventional grid-based interpretation is not applicable due to lack of lateral continuity in reservoir properties?Can we distinguish fluids within each reservoir pools?Can we extrapolate reservoir parameters observed at drilled locations to the entire field using 3D seismic data to build a 3D reservoir model?Using new 3D seismic attributes such as bright spot indicators, attenuation and edge enhancing volumes coupled with 6 AVO (Amplitude Versus Offset) volumes integrated into a single class cube of reservoir properties, made the mapping of reservoir pools possible over the entire data set. In addition, four fluid types, as observed in more than 20 reservoir pools were validated by final inverted results to allow lateral prediction of fluid contents in un-drilled reservoir targets. Well production data and 3D seismic inverted volume were later integrated to build a 3D reservoir model to support updated volumetrics reserves computation and to define additional targets for exploration drilling, additional well planning and to define a water injection plan for pools already in production.


2007 ◽  
Vol 10 (03) ◽  
pp. 312-331 ◽  
Author(s):  
Christopher R. Clarkson ◽  
R. Marc Bustin ◽  
John P. Seidle

Summary Coalbed-methane (CBM) reservoirs commonly exhibit two-phase-flow (gas plus water) characteristics; however, commercial CBM production is possible from single-phase (gas) coal reservoirs, as demonstrated by the recent development of the Horseshoe Canyon coals of western Canada. Commercial single-phase CBM production also occurs in some areas of the low-productivity Fruitland Coal, south-southwest of the high-productivity Fruitland Coal Fairway in the San Juan basin, and in other CBM-producing basins of the continental United States. Production data of single-phase coal reservoirs may be analyzed with techniques commonly applied to conventional reservoirs. Complicating application, however, is the unique nature of CBM reservoirs; coal gas-storage and -transport mechanisms differ substantially from conventional reservoirs. Single-phase CBM reservoirs may also display complex reservoir behavior such as multilayer characteristics, dual-porosity effects, and permeability anisotropy. The current work illustrates how single-well production-data-analysis (PDA) techniques, such as type curve, flowing material balance (FMB), and pressure-transient (PT) analysis, may be altered to analyze single-phase CBM wells. Examples of how reservoir inputs to the PDA techniques and subsequent calculations are modified to account for CBM-reservoir behavior are given. This paper demonstrates, by simulated and field examples, that reasonable reservoir and stimulation estimates can be obtained from PDA of CBM reservoirs only if appropriate reservoir inputs (i.e., desorption compressibility, fracture porosity) are used in the analysis. As the field examples demonstrate, type-curve, FMB, and PT analysis methods for PDA are not used in isolation for reservoir-property estimation, but rather as a starting point for single-well and multiwell reservoir simulation, which is then used to history match and forecast CBM-well production (e.g., for reserves assignment). CBM reservoirs have the potential for permeability anisotropy because of their naturally fractured nature, which may complicate PDA. To study the effects of permeability anisotropy upon production, a 2D, single-phase, numerical CBM-reservoir simulator was constructed to simulate single-well production assuming various permeability-anisotropy ratios. Only large permeability ratios (>16:1) appear to have a significant effect upon single-well production characteristics. Multilayer reservoir characteristics may also be observed with CBM reservoirs because of vertical heterogeneity, or in cases where the coals are commingled with conventional (sandstone) reservoirs. In these cases, the type-curve, FMB, and PT analysis techniques are difficult to apply with confidence. Methods and tools for analyzing multilayer CBM (plus sand) reservoirs are presented. Using simulated and field examples, it is demonstrated that unique reservoir properties may be assigned to individual layers from commingled (multilayer) production in the simple two-layer case. Introduction Commercial single-phase (gas) CBM production has been demonstrated recently in the Horseshoe Canyon coals of western Canada (Bastian et al. 2005) and previously in various basins in the US; there is currently a need for advanced PDA techniques to assist with evaluation of these reservoirs. Over the past several decades, significant advances have been made in PDA of conventional oil and gas reservoirs [select references include Fetkovich (1980), Fetkovich et al. (1987), Carter (1985), Fraim and Wattenbarger (1987), Blasingame et al. (1989, 1991), Palacio and Blasingame (1993), Fetkovich et al. (1996), Agarwal et al. (1999), and Mattar and Anderson (2003)]. These modern methods have greatly enhanced the engineers' ability to obtain quantitative information about reservoir properties and stimulation/damage from data that are gathered routinely during the producing life of a well, such as production data and, in some instances, flowing pressure information. The information that may be obtained from detailed PDA includes oil or gas in place (GIP), permeability-thickness product (kh), and skin (s), and this can be used to supplement information obtained from other sources such as PT analysis, material balance, and reservoir simulation.


SPE Journal ◽  
2017 ◽  
Vol 22 (04) ◽  
pp. 1261-1279 ◽  
Author(s):  
Shingo Watanabe ◽  
Jichao Han ◽  
Gill Hetz ◽  
Akhil Datta-Gupta ◽  
Michael J. King ◽  
...  

Summary We present an efficient history-matching technique that simultaneously integrates 4D repeat seismic surveys with well-production data. This approach is particularly well-suited for the calibration of the reservoir properties of high-resolution geologic models because the seismic data are areally dense but sparse in time, whereas the production data are finely sampled in time but spatially averaged. The joint history matching is performed by use of streamline-based sensitivities derived from either finite-difference or streamline-based flow simulation. For the most part, earlier approaches have focused on the role of saturation changes, but the effects of pressure have largely been ignored. Here, we present a streamline-based semianalytic approach for computing model-parameter sensitivities, accounting for both pressure and saturation effects. The novelty of the method lies in the semianalytic sensitivity computations, making it computationally efficient for high-resolution geologic models. The approach is implemented by use of a finite-difference simulator incorporating the detailed physics. Its efficacy is demonstrated by use of both synthetic and field applications. For both the synthetic and the field cases, the advantages of incorporating the time-lapse variations are clear, seen through the improved estimation of the permeability distribution, the pressure profile, the evolution of the fluid saturation, and the swept volumes.


Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 1052
Author(s):  
Baozhong Wang ◽  
Jyotsna Sharma ◽  
Jianhua Chen ◽  
Patricia Persaud

Estimation of fluid saturation is an important step in dynamic reservoir characterization. Machine learning techniques have been increasingly used in recent years for reservoir saturation prediction workflows. However, most of these studies require input parameters derived from cores, petrophysical logs, or seismic data, which may not always be readily available. Additionally, very few studies incorporate the production data, which is an important reflection of the dynamic reservoir properties and also typically the most frequently and reliably measured quantity throughout the life of a field. In this research, the random forest ensemble machine learning algorithm is implemented that uses the field-wide production and injection data (both measured at the surface) as the only input parameters to predict the time-lapse oil saturation profiles at well locations. The algorithm is optimized using feature selection based on feature importance score and Pearson correlation coefficient, in combination with geophysical domain-knowledge. The workflow is demonstrated using the actual field data from a structurally complex, heterogeneous, and heavily faulted offshore reservoir. The random forest model captures the trends from three and a half years of historical field production, injection, and simulated saturation data to predict future time-lapse oil saturation profiles at four deviated well locations with over 90% R-square, less than 6% Root Mean Square Error, and less than 7% Mean Absolute Percentage Error, in each case.


2021 ◽  
Author(s):  
Vil Syrtlanov ◽  
Yury Golovatskiy ◽  
Ivan Ishimov

Abstract In this paper the simplified way is proposed for predicting the dynamics of liquid production and estimating the parameters of the oil reservoir using diagnostic curves, which are a generalization of analytical approaches, partially compared with the results of calculations on 3D simulation models and with actual well production data.


2021 ◽  
Author(s):  
Helmi Pratikno ◽  
W. John Lee ◽  
Cesario K. Torres

Abstract This paper presents a method to identify switch time from end of linear flow (telf) to transition or boundary-dominated flow (BDF) by utilizing multiple diagnostic plots including a Modified Fetkovich type curve (Eleiott et al. 2019). In this study, we analyzed publicly available production data to analyze transient linear flow behavior and boundary-dominated flow from multiple unconventional reservoirs. This method applies a log-log plot of rate versus time combined with a log-log plot of rate versus material balance time (MBT). In addition to log-log plots, a specialized plot of rate versus square root of time is used to confirm telf. A plot of MBT versus actual time, t, is provided to convert material balance time to actual time, and vice versa. The Modified Fetkovich type curve is used to estimate decline parameters and reservoir properties. Applications of this method using monthly production data from Bakken and Permian Shale areas are presented in this work. Utilizing public data, our comprehensive review of approximately 800 multi-staged fractured horizontal wells (MFHW) from North American unconventional reservoirs found many of them exhibiting linear flow production characteristics. To identify end of linear flow, a log-log plot of rate versus time alone is not sufficient, especially when a well is not operated in a consistent manner. This paper shows using additional diagnostic plots such as rate versus MBT and specialized plots can assist interpreters to better identify end of linear flow. With the end of linear flow determined for these wells, the interpreter can use the telf to forecast future production and estimate reservoir properties using the modified type curve. These diagnostic plots can be added to existing production analysis tools so that engineers can analyze changes in flow regimes in a timely manner, have better understanding of how to forecast their wells, and reduce the uncertainty in estimated ultimate recoveries related to decline parameters.


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