The Integration of Analytical P/Z Material Balance Method with Static Modeling and Integrated Asset Model IAM to Generate Reliable Forecasting for a Giant Onshore Gas Field in Abu Dhabi

2021 ◽  
Author(s):  
Bondan Bernadi ◽  
Yuni Budi Pramudyo ◽  
Fatima Omar Alawadhi ◽  
Alia Belal Zuwaid Belal Al Shamsi ◽  
Shamma Jasem Al Hammadi ◽  
...  

Abstract FGIIP (Field Gas Initially in Place) is one of the most essential elements in building dependable static and Integrated Asset Model (IAM). A good estimation of FGIIP will improve history matching and generate reliable forecast. The mature gas field producing under depletion mode is an ideal example where P/Z technique can fit well to re-estimate the FGIIP. Even more, the estimation is also important to narrow down FGIIP uncertainties that initially existed in static model. Reliable FGIIP estimation is achieved by performing multiple P/Z calculations. The process involves dividing reservoir into key areas and each area is represented by individual P/Z prior to summing-up all P/Z to get the total FGIIP. Several scenarios are developed by defining key areas based on permeability variation, areal distribution and PVT behavior. The best FGIIP estimation is then fed back into the static model to generate numerous realizations considering the static uncertainties to produce the same FGIIP. Static models with realistic distribution of properties and good history match are used in the IAM model to generate forecast. The giant onshore gas field is highly heterogeneous having permeability, lateral composition variation and dynamic interaction between wells. To ensure that the heterogeneity observed in the field is honored, multiple key areas are defined by making areal sectorization and lateral PVT variation when estimating FGIIP with P/Z approach. Communication between areas was evidenced from the sectoral P/Z. The field history matching was improved after applying the new estimated FGIIP. It was observed that the sectoral history matching both for production and pressure matches from some selected realizations built in static model resulted in better matches. Succinctly the re-evaluation of static derived FGIIP with P/Z method for the mature gas field was able to reduce the uncertainty range that initially existed. Incorporating the correct estimation of FGIIP in IAM has helped to yield reliable forecast and has enabled the asset to plan proper work programs for further field development. Analytical material balance with P/Z is very applicable for mature gas reservoirs producing under depletion mode. The approach is worth doing to narrow down the uncertainty range that was previously calculated. Moreover, the integration of analytical P/Z with static and dynamic model (IAM) has achieved more reliable forecasting of the mature gas field to proceed with further development plan.

1999 ◽  
Vol 2 (04) ◽  
pp. 385-392 ◽  
Author(s):  
Jacques Hagoort ◽  
Rob Hoogstra

Summary This paper presents a robust and rigorous method for the numerical solution of the material balance equations of compartmented gas reservoirs. The method is based on the integral form of the material balance equations and employs an implicit, iterative solution procedure. The proposed method enables extension of traditional p/z analysis of single gas reservoirs to complex, compartmented gas reservoirs. Example calculations of the depletion of a compartmented reservoir show how the p/z is affected by crossflow, reservoir size, and depletion rate. The depletion behavior can be rationalized by the observation that depletion of a compartmented reservoir at a constant rate tends to develop a semisteady state. A field example is presented that illustrates the capabilities of the extended material balance for the analysis of the past performance of compartmented reservoirs. Introduction Material balance analysis is a standard reservoir engineering tool for the analysis of the performance of oil and gas reservoirs. Applied to single, tank-type gas reservoirs, the material balance yields a characteristic relationship between the ratio of pressure to z factor (p/z) and cumulative gas production.1 In the ideal case of volumetric depletion, i.e., no changes in the hydrocarbon pore volume during depletion, this relation simplifies to a straight line. A relatively new development is the application of material balance analysis to more complex, compartmented reservoirs.2–5 A compartmented reservoir is defined here as a reservoir that consists of two or more distinct reservoirs that are in hydraulic communication. A well-known example is a faulted reservoir made up of different fault blocks separated by partially sealing faults. For the purpose of a material balance analysis, a compartmented reservoir may be modeled as an ensemble of individual tank-type reservoirs, which are connected to one another by thin permeable barriers.2 Each compartment is described by its own material balance, which is coupled to the material balance of neighboring compartments through influx or efflux of gas across the common boundaries. Application of the material balance method to compartmented reservoirs requires a fast, robust, and rigorous method for solving the system of coupled material balance equations. This is the subject of the paper. Hower and Collins2 presented analytical solutions of the material balance equations for a compartmented reservoir consisting of just two reservoirs. Their solutions hold good under rather restrictive conditions: constant offtake rate from only one reservoir compartment, volumetric depletion, and constant gas properties. Yet the analytical solutions clearly demonstrated the basic features of the depletion of compartmented reservoirs. Lord and Collins3 generalized the material balance method to multicompartment reservoirs. They solved the material balance equations numerically, without introducing any simplifying assumptions and conditions. They formulated the equations as a system of coupled first-order ordinary differential equations in the pressure. The solution of this system then boils down to numerically solving an initial value problem, for which the authors used the Burlisch-Stoer method. No details were presented on the implementation of this method. Lord et al.4 applied the extended material balance method to the compartmented gas reservoirs in the Frio formation in South Texas. Payne5 applied the multicompartment reservoir model to single, tight gas reservoirs. He solved the material balance equations by means of an explicit method, ignoring changes in the flow across boundaries and gas properties during a timestep. For the calculation of the crossflow between compartments, Payne used the pressure squared formulation. Payne's calculation method is simple and straightforward, and lends itself very well for implementation in a spreadsheet program. However, the explicit calculation scheme and the use of the pressure-squared approximation might give rise to unacceptable errors. In this paper, we present a simple but rigorous numerical method for the solution of the material balance equations for compartmented gas reservoirs. It is based on the integral form of the material balance equation for each individual compartment, expressed in cumulative quantities, instead of the differential form as used by Lord and Collins. The solution method employs an implicit calculation scheme that properly accounts for the pressure dependency of gas properties. For reasons of clarity and brevity, we restrict ourselves to gas reservoirs that consist of two compartments. However, the method can be readily generalized to multi-compartment reservoirs. To illustrate the method we present examples of a compartmented material balance analysis applied in both the prediction mode and in the history-matching mode. The prediction calculations bring out the depletion characteristics of a typical compartmented reservoir. In the history match example, we illustrate the use of the compartmented reservoir model for the analysis of the observed pressure behavior of a real-life compartmented reservoir. The main advantage of the numerical solution method presented here over previous work is its simplicity. The method can be easily incorporated into existing material balance analysis programs, thereby extending the classic "p over z" analysis to more complex, compartmented reservoir systems. In addition, because of its simplicity the method lends itself very well for automatic history matching of observed reservoir performance. The method is recommended for a first analysis of the performance of compartmented gas reservoirs. Depending on the results a more elaborate analysis may be required by means of a more sophisticated 3D, multigridblock reservoir simulator.


2013 ◽  
Vol 275-277 ◽  
pp. 456-461
Author(s):  
Lei Zhang ◽  
Lai Bing Zhang ◽  
Bin Quan Jiang ◽  
Huan Liu

The accurate prediction of the dynamic reserves of gas reservoirs is the important research content of the development of dynamic analysis of gas reservoirs. It is of great significance to the stable and safe production and the formulation of scientific and rational development programs of gas reservoirs. The production methods of dynamic reserves of gas reservoirs mainly include material balance method, unit pressure drop of gas production method and elastic two-phase method. To clarify the characteristics of these methods better, in this paper, we took two typeⅠwells of a constant volume gas reservoir as an example, the dynamic reserves of single well controlled were respectively calculated, and the results show that the order of the calculated volume of the dynamic reserves by using different methods is material balance method> unit pressure drop of gas production method >elastic two-phase method. Because the material balance method is a static method, unit pressure drop of gas production method and elastic two-phase method are dynamic methods, therefore, for typeⅠwells of constant volume gas reservoirs, when the gas wells reached the quasi-steady state, the elastic two-phase method is used to calculate the dynamic reserves, and when the gas wells didn’t reach the quasi-steady state, unit pressure drop of gas production method is used to calculate the dynamic reserves. The conclusion has some certain theoretical value for the prediction of dynamic reserves for constant volume gas reservoirs.


2021 ◽  
Author(s):  
Bashirul Haq

Abstract Sour gas reservoirs are vital sources for natural gas production. Sulphur deposition in the reservoir reduces a considerable amount of gas production due to permeability reduction. Consequently, well health monitoring and early prediction of Sulphur deposition are crucial for effective gas production from a sour gas reservoir. Dynamic gas material balance analysis is a useful technique in calculating gas initially in place utilizing the flowing wellhead or bottom hole pressures and rates during the well's lifetime. The approach did not apply to monitor a producing gas's health well and detect Sulphur deposition. This work aims to (i) modify dynamic gas material balance equation by adding the Sulphur deposition term, (ii) build a model to predict and validate the issue utilizing the modified equation. A unique form of the flowing material balance is developed by including Sulphur residue term. The curve fitting tool and modified flowing gas material balance are applied to predict well-expected behaviour. The variation between expected and actual performance indicates the health issue of a well. Initial, individual components of the model are tested. Then the model is validated with the known values. The workflow is applied to active gas field and correctly detected the health issue. The novel workflow can accurately predict Sulphur evidence. Besides,the workflow can notify the production engineers to take corrective measures about the subject. Keywords: Sulfur deposition, Dynamic gas material balance analysis, Workflow


2019 ◽  
Vol 8 (4) ◽  
pp. 1484-1489

Reservoir performance prediction is important aspect of the oil & gas field development planning and reserves estimation which depicts the behavior of the reservoir in the future. Reservoir production success is dependent on precise illustration of reservoir rock properties, reservoir fluid properties, rock-fluid properties and reservoir flow performance. Petroleum engineers must have sound knowledge of the reservoir attributes, production operation optimization and more significant, to develop an analytical model that will adequately describe the physical processes which take place in the reservoir. Reservoir performance prediction based on material balance equation which is described by Several Authors such as Muskat, Craft and Hawkins, Tarner’s, Havlena & odeh, Tracy’s and Schilthuis. This paper compares estimation of reserve using dynamic simulation in MBAL software and predictive material balance method after history matching of both of this model. Results from this paper shows functionality of MBAL in terms of history matching and performance prediction. This paper objective is to set up the basic reservoir model, various models and algorithms for each technique are presented and validated with the case studies. Field data collected related to PVT analysis, Production and well data for quality check based on determining inconsistencies between data and physical reality with the help of correlations. Further this paper shows history matching to match original oil in place and aquifer size. In the end conclusion obtained from different plots between various parameters reflect the result in history match data, simulation result and Future performance of the reservoir system and observation of these results represent similar simulation and future prediction plots result.


1994 ◽  
Author(s):  
S. L. West ◽  
P. J. R. Cochrane

Tight shallow gas reservoirs in the Western Canada Basin present a number of unique challenges in accurately determining reserves. Traditional methods such as decline analysis and material balance are inaccurate due to the formations' low permeabilities and poor pressure data. The low permeabilities cause long transient periods not easily separable from production decline using conventional decline analysis. The result is lower confidence in selecting the appropriate decline characteristics (exponential or harmonic) which significantly impacts recovery factors and remaining reserves. Limited, poor quality pressure data and commingled production from the three producing zones results in non representative pressure data and hence inaccurate material balance analysis. This paper presents the merit of two new methods of reserve evaluation which address the problems described above for tight shallow gas in the Medicine Hat field. The first method applies type curve matching which combines the analytical pressure solutions of the diffusivity equation (transient) with the empirical decline equation. The second method is an extended material balance which incorporates the gas deliverability theory to allow the selection of appropriate p/z derivatives without relying on pressure data. Excellent results were obtained by applying these two methodologies to ten properties which gather gas from 2300 wells. The two independent techniques resulted in similar production forecasts and reserves, confirming their validity. They proved to be valuable, practical tools in overcoming the various challenges of tight shallow gas and in improving the accuracy in gas reserves determination in the Medicine Hat field.


Lithosphere ◽  
2021 ◽  
Vol 2021 (Special 1) ◽  
Author(s):  
Lixia Zhang ◽  
Yingxu He ◽  
Chunqiu Guo ◽  
Yang Yu

Abstract Determination of gas in place (GIP) is among the hotspot issues in the field of oil/gas reservoir engineering. The conventional material balance method and other relevant approaches have found widespread application in estimating GIP of a gas reservoir or well-controlled gas reserves, but they are normally not cost-effective. To calculate GIP of abnormally pressured gas reservoirs economically and accurately, this paper deduces an iteration method for GIP estimation from production data, taking into consideration the pore shrinkage of reservoir rock and the volume expansion of irreducible water, and presents a strategy for selecting an initial iteration value of GIP. The approach, termed DMBM-APGR (dynamic material balance method for abnormally pressured gas reservoirs) here, is based on two equations: dynamic material balance equation and static material balance equation for overpressured gas reservoirs. The former delineates the relationship between the quasipressure at bottomhole pressure and the one at average reservoir pressure, and the latter reflects the relationship between average reservoir pressure and cumulative gas production, both of which are rigidly demonstrated in the paper using the basic theory of gas flow through porous media and material balance principle. The method proves effective with several numerical cases under various production schedules and a field case under a variable rate/variable pressure schedule, and the calculation error of GIP does not go beyond 5% provided that the production data are credible. DMBM-APGR goes for gas reservoirs with abnormally high pressure as well as those with normal pressure in virtue of its strict theoretical foundation, which not only considers the compressibilities of rock and bound water, but also reckons with the changes in production rate and variations of gas properties as functions of pressure. The method may serve as a valuable and reliable tool in determining gas reserves.


2020 ◽  
Vol 496 (1) ◽  
pp. 199-207 ◽  
Author(s):  
Tor Anders Knai ◽  
Guillaume Lescoffit

AbstractFaults are known to affect the way that fluids can flow in clastic oil and gas reservoirs. Fault barriers either stop fluids from passing across or they restrict and direct the fluid flow, creating static or dynamic reservoir compartments. Representing the effect of these barriers in reservoir models is key to establishing optimal plans for reservoir drainage, field development and production.Fault property modelling is challenging, however, as observations of faults in nature show a rapid and unpredictable variation in fault rock content and architecture. Fault representation in reservoir models will necessarily be a simplification, and it is important that the uncertainty ranges are captured in the input parameters. History matching also requires flexibility in order to handle a wide variety of data and observations.The Juxtaposition Table Method is a new technique that efficiently handles all relevant geological and production data in fault property modelling. The method provides a common interface that is easy to relate to for all petroleum technology disciplines, and allows a close cooperation between the geologist and reservoir engineer in the process of matching the reservoir model to observed production behaviour. Consequently, the method is well suited to handling fault property modelling in the complete life cycle of oil and gas fields, starting with geological predictions and incorporating knowledge of dynamic reservoir behaviour as production data become available.


2020 ◽  
pp. 3252-3265
Author(s):  
Nagham Jasim ◽  
Sameera M. Hamd-Allah ◽  
Hazim Abass

Increasing hydrocarbon recovery from tight reservoirs is an essential goal of oil industry in the recent years. Building real dynamic simulation models and selecting and designing suitable development strategies for such reservoirs need basically to construct accurate structural static model construction. The uncertainties in building 3-D reservoir models are a real challenge for such micro to nano pore scale structure. Based on data from 24 wells distributed throughout the Sadi tight formation. An application of building a 3-D static model for a tight limestone oil reservoir in Iraq is presented in this study. The most common uncertainties confronted while building the model were illustrated. Such as accurate estimations of cut-off permeability and porosity values. These values directly affect the calculation of net pay thickness for each layer in the reservoir and consequently affect the target of estimating reservoir initial oil in place (IOIP). Also, the main challenge to the static modeling of such reservoirs is dealing with tight reservoir characteristics which cause major reservoir heterogeneity and complexities that are problematic to the process of modeling reservoir simulation. Twenty seven porosity and permeability measurements from Sadi/Tanuma reservoir were used to validate log interpretation data for model construction. The results of the history matching process of the constructed dynamic model is also presented in this paper, including data related to oil production, reservoir pressure, and well flowing pressure due to available production.


2019 ◽  
Vol 38 (2) ◽  
pp. 519-532
Author(s):  
Guofeng Han ◽  
Min Liu ◽  
Qi Li

This paper presents an improved flowing material balance method for unconventional gas reservoirs. The flowing material balance method is widely used to estimate geological reserves. However, in the case of the unconventional gas reservoirs, such as coalbed methane reservoirs and shale gas reservoirs, the conventional method is inapplicable due to the gas adsorption on the organic pore surface. In this study, a material balance equation considering adsorption phase volume is presented and a new total compressibility is defined. A pseudo-gas reservoir is simulated and the results were compared with the existing formulations. The results show that the proposed formulation can accurately get the geological reserves of adsorbed gas reservoirs. Furthermore, the results also show that the volume of the adsorbed phase has a significant influence on the analysis, and it can only be ignored when the Langmuir volume is negligible.


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