What are the most effective methods for estimating original oil in place and recovery factor?

Volumetric method mostly used in prospective and contingent recourse estimation. Probabilistic method (P90, P50, P10) may be applied to any volume, it is most often applied to volumetric calculations in the early phases of an exploitation and development project.

In general volumetric methods are more cost effective at any project stage, the bottomline will be always the availablity and accuracy of input data. However, in a more complex setting in both geology and production mechanism, is always better to consider reservoir simulation.

The most effective methods for estimating original oil in place (OOIP) and recovery factor involve a combination of reservoir simulation, material balance calculations, decline curve analysis, and integration of well performance data. These methods consider reservoir properties, fluid behavior, and historical production data to provide reliable estimates of OOIP and recovery factors for effective reservoir management and development planning.

Volumetric and material balance. Volumetric estimation relies on reservoir mapping, petrophysical properties, and delineating reservoir. Due to uncertainties in reservoir description, a probabilistic approach is often adopted. Material balance, utilizes reservoir performance data to independently estimate in-place fluids, allowing for comparison with volumetric estimates. Material balance accounts for "dynamic oil," which refers to oil affected by reservoir pressure changes due to production. However, it may not account for isolated reservoir compartments. Reservoir simulation isn't suitable for direct OOIP calculation as it requires the OOIP and reservoir drive mechanism as input via a detailed geological and petrophysical description

The efficiently of the method used strongly depends on the stage of the asset. For green fields were production data is lacking the volumetric method is effective. Data required for the estimatation are seismic data for estimating area of the asset, the porosity of the reservoir which indicates the portion of the reservoir that is occupy by fluid hence giving a measure of the storage capacity The part of the porosity that is occupied by hydrocarbon estimated as 1 - Sw .the net-to-gross ratio indicating that part of the reservoir that can economically produce hydrocarbon and the formation volume factor which as a correction factor for the gas lost due to pressure reduction when pressure is reduced.

Material balance works usually quite good in gas reservoir. The dynamic OGIP from a P/z vs Gp plot in most of the cases is very reliable.

Comienzo con afirmar que, cualquier método de cálculo, puede ser util, siempre que se tenga una buena caracterización de Yacimientos y se disponga de información capturada que permita fortalecer y confiar en los cálculos de OIP y factores de Recobro. Ahora bien, cuando piensas en hacer algún calculo de este de Volúmenes y factores de recobro, también debe evaluarse que tipo de cálculo requiere la.empresa, si un cálculo rápido menos tiempo y recurso, como una balance de materia, un cálculo volumetrico, algun pronostico por curvas de declinación, es decir, algún cálculo convencional, o sí se dispone de más tiempo y recursos para cálculos más sofisiticado como la construcción de un modelo 3D, que te permita hacer un estudio integrado.

Material balance calculation is an excellent tool for estimating gas reserves. If a reservoir comprises a closed system and contains single-phase gas, the pressure in the reservoir will decline proportionately to the amount of gas produced. Unfortunately, sometimes bottom water drive in gas reservoirs contributes to the depletion mechanism, altering the performance of the non-ideal gas law in the reservoir.

Material Balance is very reliable, but we need to be sure that cumulative production was big enough to put all production mechanisms available on action. For reserves estimation, we can use very complex numerical models, but the classical DCA is mandatory as a double-check.

Decline curve analysis is used to predict future production of oil and gas with the assumption that past production trends will continue in the future. The analysis can help determine the original oil in place (OOIP) and the recovery factor by analyzing the production trend over time. The Decline Curve analysis cannot be used in the very early stage of production as there will be less data and estimating the correct trend can be erroneous as it relies on the past data.

Decline analysis (DCA) requires an understanding of the factors controlling the decline. For example, to apply DCA in waterflood applications oil rate should be driven by relative permeability. Factors such as facilities constraints, gravity override, viscous fingering, channeling, stratification and compartmentalization should not be controlling oil rates. Scattering and high noise/signal ratio because of infill drilling, well interventions and interference, injection/production rate changes, compromise the analysis. Before water breakthrough (wc<50% as a rule of thumb) DCA is not a good choice because pressurization and volumetric sweep effects are likely to dominate oil production, in fact, oil production at this stage may be inclining

Reserves estimation is crucial to oil and gas industry as it involves all financial aspects of the petroleum companies. Among reserves classification, proved reserves always capture the most attention because most value is attached to it. By the SPE definition, proved reserves must be estimated by reliable methods that have a high-at least a 90% probability (P90) - that the actual quantities recovered will equal or exceed the estimate. Decline curve analysis (DCA) is one of the most commonly used methods for proved reserves estimation throughout the industry. Through the DCA, a production history is fitted with a trend line, then the line will be extrapolated to an economic limit for the reserves estimation.

Numerical reservoir modeling is primarily useful for discovering and developing physical and operational proposals for improving RF’s or EURs. It is typically not the method of choice for determining reserves, unless it has been constrained by alternate processes, such as DCA. Computational modeling algorithms utilize two categories of data——measured (or derived from measurements), and “nebulous variables” (those that are not practical or fiscally reasonable to measure). Therefore, analog processes such as DCA must be applied to rigorously bracket the nebulous variables and constants and force-match the base case to actual decline history.

The simulation method applies the principle of flow through a porous medium owning to pressure differential. It is based on Darcy's law, mass conservation equation and state thermodynamic properties of the fluid . This results in a series of differential equations which is computed using high power computers. The geometry of the reservoir is captured as a series of grids, The grids represents the hydraulic flow units in the reservoir. Wells are the represented as input (injection Wells) and outputs (production Wells). This model is the simulated in order to determine the most effective and economical way of explaining the reservoir.

The Geo runs volumetrics. The Geo and RE head out for coffee. The RE casually hands over the MatBal estimates, along with some DCA and a few other smell tests. The Geo then works out where to sneak in a few fudge factors to bring volumetrics back to reality. The recovery factor? Oh, that's pulled from some ancient tome based on the field type, and a little hand-waving about analogs is thrown in for good measure.

Due to subsurface uncertainties underlying each method, it is best practice to compare and contrast the results from various methods. For instance, at an early stage of field appraisal, volumetric methods, which have a large range of uncertainty, would be used to estimate hydrocarbons in place. Over time, as we start to acquire sources dynamic data (eg: production tests), this new data can be used to calibrate dynamic models such as material balance or simulation models, which can help narrow the range of in place uncertainty. Finally, as we acquire even more dynamic production data, we can generate decline curve models which helps estimate EUR. These results should be reviewed alongside earlier in place estimates for consistency.

Otro método a considerar es el rate transient analysis (RTA). En este análisis se emplean presiones de fondo fluyendo y la producción del pozo. También se le conoce como balance de materia fluyente. Se obtienen muy buenos resultados a nivel de pozo y del yacimiento. Se puede realizar en un sólo pozo, o en múltiples pozos.

Determining OOIP and RF can be assessed based on the stage of exploration and development, depending on the amount of data available. At early stages without much data, the analogy method works just fine but not accurate enough. In later stages provided well and seismic data, the volumetric method will be handy. As the fields life progresses, production data can be added, and methods such as decline curve and MBAL can be used. The most effective way to know the amount oil in place, is definitely at the end of production, when no further production can be done. Then, we can confidently tell how much oil there was based on what has already been produced, and how much is left behind based on RST data. Each method therefore helps

The volumetric method of estimating resources and reserves are mainly employed for green fields where critical and production data are not yet available. The material balance method is applied after some time where production data is available. The material balance method also reveals the drive mechanism that governed production. It is therefore very important that accurate pressure and temperature data as well as production data is available. At the later stage of the reservoir the decline curve method can be used since production data as well as well test data are readily available.

As production and pressure data from a field become available, decline analysis and material balance calculations, become the predominant methods of calculating reserves. These methods greatly reduce the uncertainty in reserves estimates; however, during early depletion, caution should be exercised in using them. Decline curve relationships are empirical, and rely on uniform, lengthy production periods.