In heterogeneous reservoirs like Hassi Messaoud, the exact interwell location of each reservoir sandstone body can not be in most cases easily located, and the potential of drilling unsuccessful production wells is usually present. In this situation a reservoir characterization model with usable uncertainties is needed.
Conventional modeling techniques fail to quantify heterogeneities in lateral direction, however horiontal well data appear to compensate for this lack of information, providing some knowledge about variability of reservoir parameters, using data recorded along the horizontal drainhole of horizontal wells, hence providing adequate measurements of reservoir properties in the interwell locations.
In this study a petrophysical model was generated for the north east area of Hassi Messaoud field comprising four horizontal wells. The generated models of porosity permeability and shale distribution were in agreement with Hassi Messaoud braided fluvial depositional model. The facies lateral variations have confirmed the nonuniform depletion throughout this sector of the field, which has led to its zonation.
Once the reservoir characterization was complete, the generated model was validated using a full-field model of North East area, that involves history match of each well individually.
For each target reservoir, many geostatistical realizations can be generated by integrating seismic, sedimentology, geology, and petrophisical data with their respective uncertainties captured by these models. Traditionally, reservoir description has been interpolated at the inter well locations, using simple algorithms, which fails to capture the true geological complexity and therefore results in ineffective prediction. To address this failure in the traditional route, one needs to consider using tools which allow the user to represent more accurately the range of plausible geological cases. Stochastic modeling techniques are used to construct detailed geological description using structural information, diagenetic and depositional models, reservoir stratigraphy, log and core data, and fault and fracture information.
In most cases, adequate measurements of reservoir properties are not available to evaluate inter well variability at small scales. Information about lateral variations of reservoir parameters comes from horizontal wells or seismic data. Log data from horizontal wells have been used to improve inter well reservoir characterization, identify fractures and lateral variation of facies.
Stochastic reservoir modeling is becoming commonly used tool to describe reservoir heterogeneities. It involves the generation of images of the reservoir lithofacies and rock properties that ideally, would honor all available data (Core measurements, well logs, seismic and geological interpretations, analog outcrops, well test interpretations, etc). Certain information, like production data or effective properties derived from well tests, can not be easily incorporated into the reservoir model. Almost always, a stochastic reservoir modeling exercise will involve a hybrid technique combining the best features of a number of available algorithms. Simulated annealing is an algorithm initially developed for the solution of combinatoin optimization problems.
Generally, conventional modeling techniques fail to capture the true geological complexity of the reservoir in the lateral direction due to the lack of data in unsampled zones. In most field cases, only vertical well data representing a small fraction of the reservoir are available to describe the spatial distribution of reservoir properties. Horizontal wells, however, have emerged to quantify heterogeneities in the lateral direction because of their extended reach.