Abdulaziz A. Al-Majed

Functional networks as a new data mining predictive paradigm to predict permeability in a carbonate reservoir

Permeability prediction has been a challenge to reservoir engineers due to the lack of tools that measure it directly. The most reliable data of permeability obtained from laboratory measurements on cores do not provide a continuous profile along the depth of the formation. Recently, researchers utilized statistical regression, neural networks, and fuzzy logic to estimate both permeability and porosity from well logs. Unfortunately, due to both uncertainty and imprecision, the developed predictive modelings are less accurate compared to laboratory experimental core data. This paper presents functional networks as a novel approach to forecast permeability using well logs in a carbonate reservoir. The new intelligence paradigm helps to overcome the most common limitations of the existing modeling techniques in statistics, data mining, machine learning, and artificial intelligence communities. To demonstrate the usefulness of the functional networks modeling strategy, we briefly describe its learning algorithm through simple distinct examples. Comparative studies were carried out using real-life industry wireline logs to compare the performance of the new framework with the most popular modeling schemes, such as linear/nonlinear regression, neural networks, and fuzzy logic inference systems. The results show that the performance of functional networks (separable and generalized associativity) architecture with polynomial basis is accurate, reliable, and outperforms most of the existing predictive data mining modeling approaches. Future work can be achieved using different structure of functional networks with different basis, interaction terms, ensemble and hybrid strategies, different clustering, and outlier identification techniques within different oil and gas challenge problems, namely, 3D passive seismic, identification of lithofacies types, history matching, rock mechanics, viscosity, risk assessment, and reservoir characterization.

Uncertainty analysis of Archie’s parameters determination techniques in carbonate reservoirs

Reservoir evaluation is one of the critical tasks of any reservoir exploration and field development plan. Water saturation calculated from open-hole resistivity measurements is a primary input to hydrocarbon reserves evaluation. Archie’s equation is the water saturation model for the determination of water saturation. Application of Archie equation in carbonate reservoir is not easy due to high dependency of its parameters on carbonate characteristics. Determination techniques of Archie’s parameters are relatively well known and validated for sandstone reservoirs, while carbonates are heterogeneous and a correct estimation of Archie’ parameter is important in their evaluation. In the case of carbonate rocks, there are considerable variations in texture and pore type, so, Archie’s parameters become more sensitive to pores pattern distribution, lithofacies properties and wettability. Uncertainty in Archie’s parameters will lead to non-acceptable errors in the water saturation values. Uncertainty analysis has shown that in calculating water saturation and initial oil in place, the Archie’s parameters (a, m, n) have the largest influence and Rt and Rw are the least important. The main objective of this study was to measure Archie’s parameters on 29 natural carbonate core plugs at reservoir conditions, using live oil, these core samples were taken from three wells. For this purpose, three techniques were implemented to determine Archie’s parameters; conventional technique, core Archie’s parameters estimate technique and three-dimensional technique. Water saturation profiles were generated using the different Archie parameters determined by the three techniques. These profiles have shown a significant difference in water saturation values and such difference could be mainly attributed to the uncertainty level for the calculated Archie parameters. These results highlight the importance of having accurate core analysis’s measurements performed on core samples that yield representative a, m and n values that highly influence the water saturation values.

Carbon Dioxide (CO2) Miscible Flooding in Tight Oil Reservoirs: A Case Study

The CO2 flooding is a proven enhanced oil recovery technique to obtain high oil recovery from complicated formations. It can be injected as immiscible or miscible flooding but immiscible flooding is less effective than miscible flooding. The miscible flooding process involves complex phase behaviour. The CO2 increases oil recovery by oil swelling, reduction of oil viscosity and density, the acidization of carbonate formations and miscibility effects. Multiple-contact miscibility between the injected CO2 and oil can be achieved at pressures above the minimum miscibility pressure (MMP). MMP is the pressure at which the reservoir fluid develops miscibility with CO2 and is a very important parameter in a welldesigned CO2 flooding project. This presentation will briefly address the results of CO2 miscible flooding applied to a known tight reservoir. Several CO2 miscible flooding experiments were conducted using live oil at reservoir temperature and pressure above the MMP on composite cores of the known reservoir. The MMP was determined experimentally using a slim tube device. High oil recovery from these experiments indicates that the MMP determined from slim tube studies was correct and such a high recovery is only possible if full miscibility occurs during the displacement. The analytical correlation also gave a MMP consistent with MMP determined from slim tube experiments.

Effect of overbalance pressure on formation damage

Experiments were conducted to investigate the influence of overbalance pressure on formation damage during drilling operations. An innovative ultrasonic method was employed to measure mud invasion depth. It was observed that mud invasion depth decreases with increasing overbalance pressure until it reaches a critical pressure. Beyond that, invasion depth increases with overbalance pressure. The above phenomenon reflects a strong physical relationship between overbalance pressure and mud fines and filtrate invasion depth.

SUPPORT VECTOR REGRESSION AND FUNCTIONAL NETWORKS FOR VISCOSITY AND GAS/OIL RATIO CURVES ESTIMATION

In oil and gas industry, prior prediction of certain properties is needed ahead of exploration and facility design. Viscosity and gas/oil ratio (GOR) are among those properties described through curves with their values varying over a specific range of reservoir pressures. However, the usual single point prediction approach could result into curves that are inconsistent, exhibiting scattered behavior as compared to the real curves. Support Vector Regressors and Functional Networks are explored in this paper to solve this problem. Inputs into the developed models include hydrocarbon and non-hydrocarbon crude oil compositions and other strongly correlating reservoir parameters. Graphical plots and statistical error measures, including root mean square error and average absolute percent relative error, have been used to evaluate the performance of the models. A comparative study is performed between the two techniques and with the conventional feed forward artificial neural networks. Most importantly, the predicted curves are consistent with the shapes of the physical curves of the mentioned oil properties, preserving the need of such curves for interpolation and ensuring conformity of the predicted curves with the conventional properties.

Factors affecting pseudo relative permeability curves

A large number of grid cells are needed to simulate very large field reservoirs such as those in the Middle East. Pseudo relative permeability curves are used to reduce the dimensionality of reservoir simulation models and also to account for intra-cell rock property variations. Identifying the parameters affecting pseudo relative permeability curves is very important so that the model cells can be grouped in different categories in which appropriate pseudo relative permeabilities are generated for each group. The objective of this study is to identify the factors affecting pseudo relative permeability curves. Different reservoir rock and fluid properties were studied for an homogeneous 2D reservoir model. Validation of some curves is also done. The most pronounced effect on pseudo relative permeability curves was found to be caused by the reservoir dip angle. Layer thickness and PVT properties have some effect. Production rate and vertical to horizontal permeability ratio have no significant effect within the parameter ranges studied. While absolute permeability on low dip angle cases has no effect, absolute permeability effects on high dip angle cases needs consideration.

New Model to Predict Formation Damage due to Sulfur Deposition in Sour Gas Wells

Elemental sulfur (S8) is often present in considerable amounts in sour gas reservoirs at the reservoir conditions (pressure and temperature). For the isothermal conditions in the reservoir, the reduction in reservoir pressure below a critical value will cause the elemental sulfur to deposit in the formation. Sulfur deposition can cause severe loss in the pore space available for gas, and in turn it will affect the gas well productivity. Accurate prediction of sulfur deposition in the reservoir will help in better management of sour gas reservoirs with potential sulfur deposition problems. In this paper a new analytical model was developed to predict the formation damage due to sulfur deposition. This model can be used to study the effect of sulfur deposition on gas relative permeability, reservoir porosity, skin damage and reservoir rock wettability. The main objective of this model is to investigate the effect of radial distance on formation damage. Accurate correlations of different rock and fluid properties were used in this model for improved predictions. Accurate correlations of gas viscosity and gas compressibility were used, as the sulfur solubility is a strong function of gas viscosity and gas density. These correlations were used for the calculation of sulfur solubility at reservoir conditions. Model predictions showed that sulfur deposition depends on the radial distance from the well bore. The most damage occurred in the 3 ft around the wellbore. As the radial distance increases the effect of sulfur deposition becomes negligible. Unlike previous models, which neglected the effect of pressure on gas properties, accurate correlations were used in the new model. Also, various sulfur solubility correlations were tested using the new model. A reduction of 2000 psi in the reservoir pressure, causes a 40 % loss of reservoir porosity at a radial distance of 3 ft from the wellbore and almost 85 % loss in the gas relative permeability at the same distance. Introduction Elemental sulfur is often present in considerable quantities in sour gas at the reservoir pressure and temperature. The gas production decreases the reservoir pressure, and in turn the solubility of sulfur in the sour gas decreases (Kennedy and Wieland 1960). Elemental sulfur is present as a dissolved species in virtually all deep sour gas reservoirs. Sulfur precipitation is induced by a reduction in the solubility of the sulfur in the gas phase beyond its thermodynamic saturation point as a result of decrease in pressure and temperature. The change in pressure and temperature occur during production operations and can result in sulfur deposition in the reservoir, wellbore and surface facilities (Hands et al. 2002 and Shedid et al. 2006). Deposition of elemental sulfur in the near-wellbore region may significantly reduce the inflow performance of sour gas wells. Deposition of the liquid sulfur in the reservoir may impair both the reservoir porosity and permeability and results in the productivity impairment of the gas well. T he decline in the well productivity from a dry sour gas reservoir (south west Alberta) with a 16 vol. % H2S was attributed to sulfur deposition in the formation (Mei et al. 2006). Sulfur in the gas phase reacts to form a hydrogen polysulfide species at high temperatures and pressures. Deposition of elemental sulfur occurs when changes in pressure and temperature helps in the decomposition of polysulfide to elemental sulfur and H2S (Xiao et al. 2006). Sulfur deposition in the formation, especially, in the vicinity of the wellbore may significantly reduce the inflow performance of sour gas wells. Wells have become completely plugged with sulfur in certain sour gas reservoirs after several months of production. Accurate prediction and effective management of the sulfur deposition are, therefore, crucial to the economic viability of sour gas reservoirs. Many analytical and numerical models were developed to predict the effect of sulfur deposition on the inflow performance of gas wells. There are some shortcomings in previous models which may not allow for accurate prediction of

Effect of Nanoclay on Mechanical and Rheological Properties of Oil Well Cement Slurry Under HPHT Environment

In oil and gas well cementing a robust cement sheath is required to ensure long-term integrity of the wells. Successful completion of cementing job has become more complex, as drilling is being carried out in highly deviated and high pressurehigh temperature (HPHT) wells. Use of nanomaterials in enhanced oil recovery, drilling fluid, oil well cementing and other applications is being investigated. This paper presents the results of an experimental study conducted to investigate the effect of nanoclay as an additive, on the mechanical and rheological properties of TypeG cement slurry under HPHT conditions. Nanoclay based cement mixes were prepared by replacing cement with 1%, 2% and 3% nanoclay, and admixed with silica flour, and other chemical admixtures. Evolution of compressive strength, thickening time and rheological properties were measured under HPHT conditions. Nanoclay at 1% in cement slurry enhances the compressive strength with accelerated strength development at early ages. The thickening time and plastic viscosity of the nanoclay cement mixes increases significantly as the percentage of Nanoclay increases in the cement slurry.

Liquids Phase Holdup and Separation Characteristics as a Function of Well Inclination and Flowrate

The maturing Middle Eastern oil fields with natural aquifer support or water injection can pose a challenging produced water handling and disposal issues. The increased water-oil ratio also presents productivity problems: many wells will die prematurely due to increased water holdup. The produced water management cost @US

Field Based Criteria For The Design of Safe Mud Weight Window

0.50—1.00 per barrel involving millions of barrels of water (even at a modest WOR of 50% from current 30-35%) will be in billions due to the high daily oil production rate envisaged. In this paper, we focus on various aspects of downhole oil-water separation, which we believe will lessen the cost significantly. The downhole water separation technology developed and applied in the western hemisphere cannot be directly applied here because of the orders of magnitude higher production rates per