Category Archives: Simulacion de Yacimientos
PRESSURE TRANSIENT ANALYSIS (PTA)
PTA has been the primary reason for the development of the tools we use today. It was initially called Well test Interpretation. Originally this type of analysis was performed on data acquired during operations refereed to a well test. A typical well test set-up is shown in that picture, temporary equipment is installed downhole and at surface, the well is put on production under a predefined program and the diagnostic is performed, generally on a shut-in period after a stable production phase during which the producing rate was measured.
To perform a Pressure Transient Analysis the rates from the tested Wells and, where applicable, nearby wells are required. In addition the pressure response, preferably from downhole measurement, and generally acquired during pressure build-ups, are recorded. However it is always recommended to acquired the pressure response during the full production history of the test. Additional information needed includes the fluid physical properties; pressure, volume and temperatura (PVT) and possibly logs and geology.
The first PTA methods were introduced in the 1950’s with specialized plots (semilog, MDH, Horner) initially focused on a specific flow regime called Infinite Acting Radial Flow (IARF),where both well productivity
and the main reservoir properties could be determined. Specialized plots for other flow regimes (liner, bi-liner, pseudo-steady state, etc) were also developed.
In the 1970’s log type-curve matching techniques were developed to complement straight line techniques. The principle was to plot the pressure response on a log-log scale tracing paper and slide this plot over pre-printed until one was selected and matched. The choice of the type-curve and the relative position of the data on this type-curve, called the match point, were then used to calculate physical results. These methods were of poor resolution until the Bourdet Derivative was introduced.
In 1983, the bourdet derivative, the slope of the semilog plot displayed on the loglog plot considerably increased the diagnostic capability, resolution and reliability of a new generation of type-curves. However, the mid 1980 saw the development of PC (Personal Computer) based dedicated software, with the possibility of directly generating models integrating
superposition effects. These packages are based on modern pressure transient analysis and the use of sophisticated and user-friendly computer programs running on state-of-the-art PCs. Advanced mathematical models are used to match the measured pressure response to any disturbance, taking into account the complete pressure and flow rate history thus generating the exact model corresponding to the actual test history.
Models are diagnosed through pattern recognition of the different flow regimes present in a response and using the Bourdet derivative, which defines these flow regimes easily. The engineer can decide which should be the most appropriate model to apply.
The methodology has a downside in that solution found are not always unique so the engineer is challenged to search for the most consistent answer by considering all data available to him from all sources, not only the well test. Gone are the days of most straight-line analysis. MDH, Horner and other specialized analysis plots have become redundant as it is the model and the match with the real data that governs the validity of these analysis. In addition, nonlinear regression to improve results, and the development of powerful PCs, has brought the methodology to the point it is today:
The development of new analytical models in the 1980/1990’s and processor hungry numerical models in the 1990/2000’s converged with the availability of increasing volumes of reliable data and high speed desktop computers.
The application of this methodology spread rapidly beyond well tests as other field operations could produce candidate data for such processing. So the name drifted from Well Test Interpretation to the more generic term Pressure Transient Analysis, although the name Well Test (WT community, WT Forum, WT monograph) remained.
Pressure Trasient Analysis was the correct terminology because the basic process was the interpretation of the pressure signal after correction taking into account the production history (superposition time, convolution, deconvolution, etc).
Pressure Transient Analysis was about making a diagnostic, and then using this to take decisions, including remedial action on the well and/or using the resulting model to simulate future well behavior.
NUMERICAL MODELS OF OI RESERVOIRS. Numerical models are becoming increasingly popular in well test analysis, mainly because the address problems far beyond the reach of analytical and semi-analytical models. The two main areas of usage of numerical models are nonlinearities, such as multiphase or non-Darcy flow, and complex reservoir or well geometries. Numerical
models can also be used to replace rate by pressure constraints when the well flowing pressure goes below a certain point, hence avoiding the embarrassing negative pressures often generated by analytical models.
The first attempts at numerical well testing were done ad hoc across the industry by engineers using standard reservoir simulators with local grid refinement. In the early 1990’s the first industrial project involved pre-conditioning of an industry standard simulator using PEBI gridding. Since then, several technical groups have been working on numerical projects dedicated to transient analysis.
In recent years, improvements in automatic unstructured grids and the use of faster computers have allowed such models to be generated in a time that is acceptable to the end user. The change has been dramatic, the time required to calculate the solution has decreased from days to hours, then to minutes, and now, for linear diffusion problems, to seconds. Using gradient methods even nonlinear regression is possible, and improved well-to-cell models allow simulation on a logarithmic time scale with little or no numerical side effects.
Last, but not least, automatic gridding methods allow such models to be used without the need for the user to have a strong background in simulation.
The main goal of numerical models is to address complex, boundary configurations, but this part of the work is actually easily done by any simulator. The problem is to also address what is easily done by analytical models, for example, the early time response and the logarithmic sampling of the time scale. This requires, one way or the other, to get more grid cells close to the well, and this has been done using three possible means:
- Local grid refinement of Cartesian grids.
- Unstructured gridding.
- Finite elements.
When the diffusion problem to model is linear, taking the same assumption as in an analytical solution, the process only requires one interaction of the linear solver for each time step. The solution is very fast and the principle of superposition can be applied. In this case, the numerical model acts as a “super-analytical-model” which can address geometries far beyond those of an analytical model.
When the problem in nonlinear the numerical module is used more like a standard simulator, with “just” grid geometry adapted to a logarithmic time scale. The nonlinear solver is used, iterating on the linear solver.
A numerical model can also be used to change the well constraint in time. For each well, a minimum pressure is set, below which the simulator changes mode and simulates the well production for this minimum pressure.
- Predicción del flujo de caja
- Necesidad de realizar una predicción económica de determinado proyecto de la compañía petrolera
Gerenciamiento de Reservorios
- Coordinar actividades del gerenciamiento de yacimientos
- Evaluar el desempeño de los proyectos
- Interpretar/entender el comportamiento del yacimiento
- Modelar la sensibilidad a los datos estimados
- Determinar la necesidad de datos adicionales
- Estimación de vida del proyecto
- Predecir la recuperación de petróleo crudo frente al tiempo
- Comparación de diferentes procesos de recuperación
- Plan de desarrollo o cambios operativos
- Seleccione y optimizar el diseño de un determinado proyecto
- Maximizar la recuperación económica
- Cash Flow Prediction
- Need Economic Forecast of Hydrocarbon Price
- Coordinate Reservoir Management Activities
- Evaluate Project Performance
- Interpret/Understand Reservoir Behavior
- Model Sensitivity to Estimated Data
- Determine Need for Additional Data
- Estimate Project Life
- Predict Recovery versus Time
- Compare Different Recovery Processes
- Plan Development or Operational Changes
- Select and Optimize Project Design
- Maximize Economic Recovery
Specifically are mostly simple spreadsheets but versatile which can be modified according to the petrophysical parameters to be taken and results to be obtained.
There are 16 small oil programs (spreadsheets) which are:
1. KWIK. Oil program (spreadsheet) to analyze conventional oil wells, gas and tar sand which includes sand production data (pay zone), productivity and oil reserves.
2. ESP. Software oil for conventional oil and gas, including lithology, sand, net (net pay), productivity and reserves.
3. ART. Spreadsheet to analyze tar sands oil, includes sand net (net pay), productivity and reserves.
4. CORE. Oil worksheet to compare productivity data, net pay and reserves with ESP and ART, as well crossplots.
5. DST. Software to calculate the pressure oil buildup, including the methods of Horner and Ramey with plots.
6. CASH. Oil program to analyze cash flow, including a style-exploration, production forecasting and cash flow.
7. SCAL. Software for analyzing oil capillary pressure and includes crossplot to find the SWIR.
8. FRF. Oil worksheet to analyze the electrical properties records.
9. TVD. Oil program to find the True Vertical Depth (TVD) by 7 methods.
10. MECH. Software oil to find the mechanical properties and elastic constants including Poisson radius, shear, Young’s modulus and stress closure.
11. MODL. Record oil model seismic responses, including predicting the response of the fluid and rock.
12. DIP. Small oil program that includes apparent arbitrary dip and azimuth.
13. Pyrite. Small oil program that models the effects of pyrite in the resistivity and saturation of the oil reservoir rock.
14. TOC. Petroleum small tarball software that calculates the total organic content VS resistivity sonic logs, resistivity vs density.