A Method for Determining Reservoir Fluid Saturations Using Field Production Data (includes associated paper 6408 )

1975 ◽  
Vol 15 (06) ◽  
pp. 477-486
Author(s):  
J.K. Dietrich

Abstract Reliable reservoir fluid saturation data areimportant to the over-all planning for prospectivesupplemental recovery projects. A trial-and-error graphical procedure, based on the fractional flowequation and using field production data, has beendeveloped to determine these values with reasonable accuracy. Introduction The preliminary analysis of a reservoir todetermine the feasibility of supplemental recoveryoperations requires a reliable estimate of reservoir fluid saturations, and a judgment must be made asto the degree of accuracy desired. An increase inthe complexity, data requirements, andsophistication of the various available solution methods doesnot necessarily imply that the results will be moreprecise. The decision as to which solution method should be used is sometimes difficult to make.This decision should consider, among other things, engineering manpower requirements for the various alternatives, the quality of existing data, and thesensitivity of the project economics to a reasonablevariation in fluid saturation levels.Average oil, water, and gas saturations for areservoir as a whole are usually determined by apressureTroducdonhistorymatchusingconventionalmaterial-balance methods. More sophisticatednumerical simulation techniques are generally used to determine reservoir saturation distributions.Simulation work can be time consuming andexpensive when efforts are made to determineaccurately the saturation distribution by attemptingto match the individual performances of a largenumber of wells.A trial-error graphical procedure has been developed as an alternative to the moresophisticated methods. Because of its easy use, the procedure may be considered as an efficientand economical application of engineering effort forplanning purposes. An application of this techniqueis illustrated for the Ten Section field, KernCounty, Calif. RESERVOIR DESCRIPTION The Ten Section field, located near Bakersfield, Calif., was discovered in 1936; developmentprogressed continuously until 1942, at which time 126 wells had been completed within the originallyproductive area of about 2,200 acres (Fig. 1). TheTen Section structure is a gently dipping (3 deg. to 7 deg.)doubly plunging anticline. The producing measuresare the upper Miocene Stevens turbidite sands, which have been subclassified as Zones 1, 2, and 3.The Zone 2 reservoir includes the intermediateseries of these sands that are bounded above by athin continuous shale varying in thickness from 5to 10 ft and are separated from the deeper measuresby an extensive thin shale. The sand intervals ofthe upper Stevens turbidite sequence are composedof individually graded and rythmically beddeddeposits. Core observations indicate that the cyclesaverage 2 to 3 ft in thickness and that the sandscomposing each cycle display the usual turbiditevariation in grain size (grading from coarse at thebase to fine at the top). Both sands and shaleswithin Zone 2 are discontinuous and few units arecorrelative across the field.Original oil in place within the Zone 2 volume of170,000 net acre-ft is estimated to have been 91million STB. About 35 million STB of oil (38.5percent) have been produced to date. An activepartial water drive is currently maintaining reservoirpressure in most portions of the field and anultimate primary recovery efficiency of 41.5 percentof the stock tank oil originally in place should berealized. Table I lists the pertinent reservoirproperties.About 58,000 acre-ft of the crestal portion of thereservoir are currently productive (Fig. 2). Part ofthis volume has been swept by natural water influx, as evidenced by the high producing water cuts inmany of me wells. Reservoir heterogeneitiesaccount for the lack of an easily discernible commonwater level in Zone 2. SPEJ P. 477^

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):  
Elizabeth Ruiz ◽  
Brandon Thibodeaux ◽  
Christopher Dorion ◽  
Herman Mukisa ◽  
Majid Faskhoodi ◽  
...  

Abstract Optimized geomodeling and history matching of production data is presented by utilizing an integrated rock and fluid workflow. Facies identification is performed by use of image logs and other geological information. In addition, image logs are used to help define structural geodynamic processes that occurred in the reservoir. Methods of reservoir fluid geodynamics are used to assess the extent of fluid compositional equilibrium, especially the asphaltenes, and thereby the extent of connectivity in these facies. Geochemical determinations are shown to be consistent with measurements of compositional thermodynamic equilibrium. The ability to develop the geo-scenario of the reservoir, the coherent evolution of rock and contained fluids in the reservoir over geologic time, improves the robustness of the geomodel. In particular, the sequence of oil charge, compositional equilibrium, fault block throw, and primary biogenic gas charge are established in this middle Pliocene reservoir with implications for production, field extension,and local basin exploration. History matching of production data prove the accuracy of the geomodel; nevertheless, refinements to the geomodel and improved history matching were obtained by expanded deterministic property estimation from wireline log and other data. Theearly connection of fluid data, both thermodynamic and geochemical, with relevant facies andtheir properties determination enables a more facile method to incorporate this data into the geomodel. Logging data from future wells in the field can be imported into the geomodel allowingdeterministic optimization of this model long after production has commenced. While each reservoir is unique with its own idiosyncrasies, the workflow presented here is generally applicable to all reservoirs and always improves reservoir understanding.


2018 ◽  
Vol 9 (3) ◽  
pp. 427-467 ◽  
Author(s):  
Lisa Hsin ◽  
Geraldine Legendre

Abstract We present elicited production data reflecting cross-linguistic interference effects in the English wh-questions of Spanish-English bilingual children to provide a proof-of-concept for a proposed new formal analysis of such effects across cross-linguistic influence phenomena. The observed interference effects are interpreted as evidence for the Strong Integration hypothesis of bilingual grammatical architecture, in the context of independently documented facilitation and interference effects in a range of bilingual acquisition contexts. Building on an existing Optimality-Theoretic (OT) model of monolingual acquisition and a specific account of the adult grammar of wh-structures across dialects of Spanish, we propose that the individual patterns documented, in particular the sensitivity in child English to distinctions made in Spanish dialects on the basis of an argument/adjunct contrast, find a straightforward explanation in the OT model of acquisition as adapted to bilingual situations. The generalizability of the model as well as effects of exposure and dominance are discussed.


2013 ◽  
Vol 1 (2) ◽  
Author(s):  
Jacob A. Kunz ◽  
J. Rhett Mayor

Superabrasive microgrinding wheels are used for jig grinding of microstructures using various grinding approaches. The desire for increased final geometric accuracy in microgrinding leads to the need for improved process modeling and understanding. An improved understanding of the source of wheel topography characteristics leads to better knowledge of the interaction between the individual grits on the wheel and the grinding workpiece. Analytic stochastic modeling of the abrasives in a general grinding wheel is presented as a method to stochastically predict the wheel topography. The approach predicts the probability of the number of grits within a grind wheel, the individual grit locations within a given wheel structure, and the static grit density within the wheel. The stochastic model is compared to numerical simulations that imitate both the assumptions of the analytic model where grits are allowed to overlap and the more realistic scenario of a grind wheel where grits cannot overlap. A new technique of grit relocation through collective rearrangement is used to limit grit overlap. The results show that the stochastic model can accurately predict the probability of the static grit density while providing results two orders of magnitude faster than the numerical simulation techniques. It is also seen that grit overlap does not significantly impact the static grit density allowing for the simpler, faster analytic model to be utilized without sacrificing accuracy.


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