Application of Fluid Contact Match in Material Balance Study in a Water Injection Reservoir to Estimate STOOIP and Initial Reservoir Contacts

Author(s):  
Nsitie Obot ◽  
Vincent Eme
2002 ◽  
Vol 5 (01) ◽  
pp. 49-59 ◽  
Author(s):  
J.L. Pletcher

Summary Experience with material-balance data sets from the field and from simulation has revealed some procedures that can be used to improve analysis of both oil and gas reservoirs:Failure to account for a weak waterdrive can result in significant material-balance errors.The assertion of previous authors that weak waterdrive exhibits a negative slope on the Cole (gas) and Campbell (oil) plots has been confirmed. A weak waterdrive is much more unambiguous on these plots than on commonly used plots, such as the p/z plot for gas.A modified version of the Cole plot is proposed to account for formation compressibility.The reservoir drive indices are a useful tool for determining the correctness of the material-balance solution because they must sum to unity. The drive indices should never be normalized to sum to unity because this obscures their usefulness and leads to a false sense of security.A modified version of the Roach plot (for gas) is proposed that improves interpretation in some waterdrive situations.Material balance has not been replaced by reservoir simulation; rather, it is complementary to simulation and can provide valuable insights to reservoir performance that cannot be obtained by simulation. Introduction Classical material balance is one of the fundamental tools of reservoir engineering. Many authors have addressed the difficult problem of solving the material balance in the presence of a waterdrive (Refs. 1 through 5 are just a few of the more significant ones). The emphasis in the literature has been on strong and moderate waterdrives. In this paper, examples of weak waterdrives are shown in which the effects on the material balance are significant. All aquifers studied here are of the "pot aquifer" type, which is time-independent. In gas reservoirs, the plot of p/z vs. cumulative gas production, Gp, is a widely accepted method for solving the gas material balance1 under depletion-drive conditions. Extrapolation of the plot to atmospheric pressure provides a reliable estimate of original gas in place (OGIP). If a waterdrive is present, the plot often appears to be linear, but the extrapolation will give an erroneously high value for OGIP. Many authors have addressed this problem (including those in Refs. 2 and 5 through 8), especially in cases of strong or moderate waterdrives. The p/z plot is actually more ambiguous in weak waterdrives than in strong or moderate ones. The Cole plot7,9 has proven to be a valuable diagnostic tool for distinguishing between depletion-drive gas reservoirs and those that are producing under a waterdrive. The analogous plot for oil reservoirs is the Campbell plot.10 The literature has emphasized strong and moderate waterdrives, the signature shapes of which are a positive slope and a hump-shaped curve, respectively, on these plots. Previous authors have recognized that weak waterdrives can produce negative slopes on these two diagnostic plots, but this author is not aware of any example plots in the literature. This paper shows examples, using simulation and actual field data, wherein a negative slope clearly reveals a weak waterdrive. These plots are much more diagnostic than the p/z plot. Once a weak waterdrive has been diagnosed, the appropriate steps can be taken in the material-balance equations to yield more accurate results. The Cole plot assumes that formation compressibility can be neglected, which is frequently the case with gas. However, in those reservoirs in which formation compressibility is significant, a modification to the Cole plot is presented that incorporates formation compressibility and gives more accurate results. The reservoir drive indices have been used to quantify the relative magnitude of the various energy sources active in a reservoir. It is shown here that the drive indices are also a useful diagnostic tool for determining the correctness of a material balance solution because they must sum to unity. If they do not sum to unity, a correct solution has not been obtained. In some commercial material-balance software, the drive indices are automatically normalized to sum to unity, which not only obscures their usefulness but also leads to the false impression of having achieved a correct solution. The Roach plot has been presented11 as a tool for solving the gas material balance when formation compressibility is unknown, with or without the presence of waterdrive. This paper shows that for waterdrives that fit the small pot aquifer model, incorporating cumulative water production into the x-axis plotting term improves the linearity of the Roach plot and gives more accurate values for OGIP. Finally, it is argued that even in those reservoirs for which a simulation study is performed, classical material-balance evaluation should be performed on a stand-alone basis. Simulation should not be viewed as a replacement for material balance because the latter can yield valuable insights that can be obscured during simulation. Performing a separate material balance study usually will improve overall reservoir understanding and enhance any subsequent simulation study. Material balance should be viewed as a complement to simulation, not as a competing approach. In this paper, formation compressibility, cf, is assumed to be constant and unchanging over the reservoir life under investigation. References are given for recommended methods to be used in those cases in which cf is variable.


2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Zhiwang Yuan ◽  
Zhiping Li ◽  
Li Yang ◽  
Yingchun Zhang

When a conventional waterflooding characteristic curve (WFCC) is used to predict cumulative oil production at a certain stage, the curve depends on the predicted water cut at the predicted cutoff point, but forecasting the water cut is very difficult. For the reservoirs whose pressure is maintained by water injection, based on the water-oil phase seepage theory and the principle of material balance, the equations relating the cumulative oil production and cumulative water injection at the moderately high water cut stage and the ultrahigh water cut stage are derived and termed the Yuan-A and Yuan-B curves, respectively. And then, we theoretically analyze the causes of the prediction errors of cumulative oil production by the Yuan-A curve and give suggestions. In addition, at the ultrahigh water cut stage, the Yuan-B water cut prediction formula is established, which can predict the water cut according to the cumulative water injection and solve the difficult problem of water cut prediction. The application results show Yuan-A and Yuan-B curves are applied to forecast oil production based on cumulative water injection data obtained by the balance of injection and production, avoiding reliance on the water cut forecast and solving the problems of predicting the cumulative oil production of producers or reservoirs that have not yet shown the decline rule. Furthermore, the formulas are simple and convenient, providing certain guiding significance for the prediction of cumulative oil production and water cut for the same reservoir types.


1976 ◽  
Vol 16 (01) ◽  
pp. 10-16 ◽  
Author(s):  
L.K. Thomas ◽  
W.B. Lumpkin ◽  
G.M. Reheis

Abstract This paper presents the development of a general beta reservoir simulator that will model conventional (fixed bubble-point) problems as well as problems involving a variable bubble point, such as gas injection projects above the original bubble point and water injection projects resulting in a collapsing gas saturation, Provisions are included for allowing the pressure to cross the bubble point with the same relative ease as in a conventional simulator. Example problems are presented to demonstrate the utility of the model for gas and water injection problems. problems Introduction Many reservoir simulation problems involve treating a variable bubble point throughout the reservoir. For example, when gas is injected into an undersaturated reservoir, gas will go into solution, increasing the bubble point of the oil. As this oil moves away from the injector, the bubble point of surrounding areas also may increase point of surrounding areas also may increase because of mixing. During waterfloods of saturated reservoirs, the gas saturations in regions near the injectors frequently reduce to zero at pressures below the original bubble point. Thus, the bubble point will vary areally throughout the field. point will vary areally throughout the field.Recent publications have discussed certain aspects of the variable bubble-point problem. Most of these papers contain only a brief discussion of this problem. Ridings discusses the need for allowing saturation pressure to vary continuously throughout the reservoir as long as there is free gas associated with the oil. In the model presented by Cook et al., free gas saturation is monitored for saturated systems and the bubble point is set equal to the prevailing reservoir pressure when the gas saturation in a cell disappears. Bubble points for undersaturated cells are allowed to change because of the entrance of free gas and mixing. Spilletta et al. assume that a cell that is saturated or undersaturated at the beginning of a time step will remain so throughout the time step. They then solve their saturation equations for water and gas saturations. The bubble point of any undersaturated cell is adjusted to account for nonzero gas saturation, and the water saturation is modified to conserve oil. Steffensen and Sheffield devote their paper to the reservoir simulation of a collapsing gas saturation during waterflooding. In their model, blocks that have a free gas saturation at the beginning of a time step and have zero or negative gas saturations at the end of a time step are detected, and the bubble points for these cells are set equal to the estimated pressure where Sg reduced to zero. Gas saturation for these blocks is set equal to zero and S is set to 1 - S . The oil saturation in adjacent saturated grid blocks is then adjusted so that oil material balance is maintained. Mixing caused by flow between undersaturated blocks is neglected. This paper presents a comprehensive analysis of modeling variable bubble-point problems.* It treats the specific problems of simulating gas injection above the bubble point as well as waterflooding depleted reservoirs. It differs from previously reported work by accounting for the effect of bubble-point change on computed pressure change during a time step. Also, provisions are included that allow the pressure to cross the bubble point with the same relative ease as in a conventions! simulator In regard to waterflooding, mis paper differs from the work of Steffensen and Sheffield in mat it allows for bubble-point changes caused by mixing. DEVELOPMENT OF FLOW EQUATIONS To simulate the variable bubble-point problem, the expansion of the flow equations above the bubble point must include the effects of pressure and bubble point on fluid properties. Also, special consideration must be given to cells passing through the bubble point if both pressure and material-balance errors are to be eliminated. SPEJ P. 10


2010 ◽  
Author(s):  
Michael H. Stein ◽  
Ashish L. Ghotekar ◽  
S.M. Avasthi

Author(s):  
Boying Li ◽  
Yuhui Zhou ◽  
Su Li ◽  
Yiping Ye ◽  
Hongfa Liu

AbstractFault-karst reservoirs are featured by complex geological characteristics, and accurate and fast simulation of such kind of reservoirs using traditional simulator and simulation methods is pretty hard. Herein, we tried to discrete the complex fault-karst structures into one-dimensional connected units connecting the well, fracture and cave based on reservoir static physical parameters and injection-production dynamics. Two characteristic parameters, conductivity and connected volume, are proposed to characterize the inter-well connectivity and material basis. Meanwhile, the high-speed non-Darcy seepage term is introduced into the material balance equations for well-fracture-cave connected units to describe the actual seepage characteristics within the fault-karst reservoirs, and to better simulate the oil/water production dynamics. Based on this method, a fracture reservoir model of 1 injection-3 production was established. The change of oil–water action law in different injection and extraction systems under two production regimes of fixed production rate and fixed pressure is analyzed. A case study was conducted on S fault zone, where the flow of oil and gas did not follow the Darcy seepage rule and with a β value of 103–104, the single well flow pressure and oil production were perfectly matched with the real data. In addition, connected units with more prominent high-speed non-Darcy features were found to have better connectivity, which might shed light on the more accurate prediction of inter-well connectivity. Moreover, an improved injection-production well pattern and was proposed based on connectivity prediction model and reservoir engineering method to solve the problems of insufficient natural energy supply and overhigh oil production rate in Block S. Furthermore, the injection/production rate as well as the timing and cycle of water injection was predicted and optimized so as to better guide to site operations.


1998 ◽  
Vol 83 (1) ◽  
Author(s):  
Alexandre Maslennikov ◽  
Michel Masson ◽  
Vladimir Peretroukhine ◽  
Michael Lecomte

Author(s):  
Andre Albert Sahetapy Engel ◽  
Rachmat Sudibjo ◽  
Muhammad Taufiq Fathaddin

<p>The decline in production from of a field is the common problem in the oil and gas industry. One of the causes of the decrease in production is the decline of reservoir pressure. Based on the analisis result, it was found that SNP field had a weak water drive. The most dominant drive of the field was fluid expansion. In order to reduce the problem, a reservoir pressure maintenance effort was required by injecting water. In this research, the effect of water injection to reservoir pressure and cumulative production was analyzed. From the evaluation result, it was found that the existing inejection performance using one injection well to Zones A and B was not optimum. Because, the recovery factor was predicted to 29.11% only.By activating the four injection wells, the recoverty factor could be increase to 31.43%.</p>


2021 ◽  
Author(s):  
Javad Rafiee ◽  
Carlos Mario Calad Serrano ◽  
Pallav Sarma ◽  
Sebatian Plotno ◽  
Fernando Gutierrez

Abstract Allocation of injection and production by layer is required for several production and reservoir engineering workflows including reserves estimation, water injection conformance, identification of workover and infill drilling candidates, etc. In cases of commingled production, allocation to layers is unknown; running production logging tools is expensive and not always possible. The current industry practice utilizes simplified approaches such as K*H based allocation which provides a static and inaccurate approximation of the allocation factors; this manual approach requires trial and error and can take several weeks in complex fields. This paper presents a novel technique to solve this problem using a combination of reservoir physics and machine learning. The methodology is made up of four stages: Data Entry: includes production at well level (commingled), injection at layer level and injection patterns or a connectivity map (optional) Gross Match: in order to match gross production for each well, the tool solves for time-varying layer-level injection allocation factors using a total material balance equation across all wells. Phase Match: having the allocation factors from the previous step, the tool automatically tunes various petrophysical parameters (i.e. porosity, relative permeability, etc.) in the physics model for each injector-producer pair across all the connected layers to match the oil and water production in each producer. An ensemble of several models can be run simultaneously to account for the probabilistic nature of the problem. Output: The steps 2 and 3 can be performed at pattern level for all connected patterns or for the whole field. The application of the technology in a complex field with 80+ layers in Southern Argentina is demonstrated as a case study of the benefits of the adoption of the technology.


Sign in / Sign up

Export Citation Format

Share Document