Effect of Drilling Fluid Properties on Rate of Penetration

Zadaća ovoga rada je odrediti učinak svojstava bušačih fluida na brzinu bušenja u ležištu koristeći dnevne izvještaje bušenja. Na osnovi naših studija na terenu, slijedeća svojstva bušačih fluida u nejednakom omjeru utječu na brzinu bušenja: težina isplake, plastična viskoznost i koncentracija krutih čestica. Rezultat ove studije pokazuje da je čisti učinak svojstava bušačeg fluida na brzinu bušenja manji no što se smatralo. Brzina bušenja smanjuje se povećanjem plastične viskoznosti, koncentracije krutih čestica i težine isplake. Smanjenje brzine bušenja više se pripisuje povećanju dubine, zato što se povećanjem dubine povećava čvrstoća stijene i smanjuje poroznost.The scope of this work is to determine the effect of drilling fluid properties on penetration rate in a field using daily drilling reports. Based on our field studies the following drilling fluid properties affect penetration rate to varying degrees: mud weight, plastic viscosity and solid content. The result of this study shows that the net effect of drilling fluid properties on penetration rate is less than what it thought to be. Penetration rate is decreased by increasing plastic viscosity, solid content and mud weight. Decreasing the penetration rate is more attributed to increase of depth, because by increasing the depth, rock strength increases and porosity decreases

Investigating the effect of heterogeneity on infill wells

Abstract In recent years, improving oil recovery (IOR) has become an important subject for the petroleum industry. One IOR method is infill drilling, which improves hydrocarbon recovery from virgin zones of the reservoir. Determining the appropriate location for the infill wells is very challenging and greatly depends on different factors such as the reservoir heterogeneity. This study aims to investigate the effect of reservoir heterogeneity on the location of infill well. In order to characterize the effect of heterogeneity on infill well locations, some geostatistical methods, e.g., sequential gaussian simulation, have been applied to generate various heterogeneity models. In particular, different correlation ranges (R) were used to observe the effect of heterogeneity. Results revealed that an increase in correlation ranges will lead to (1) a higher field oil production total, and (2) a faster expansion of the drainage radius which consequently reduced the need for infill wells. The results of this study will help engineers to appropriately design infill drilling schemes

A Physical-based Model of Permeability/Porosity Relationship for the Rock Data of Iran Southern Carbonate Reservoirs

The prediction of porosity is achieved by using available core and log data; however, the estimation of permeability is limited to the scare core data. Hence, porosity and saturation data through the framework of flow units can be used to make an estimation of reservoir permeability. The purpose of this study is to predict the permeability of a carbonate gas reservoir by using physical-based empirical dependence on porosity and other reservoir rock properties. It is emphasized that this new relationship has a theoretical background and is based on molecular theories. It is found out that if rock samples with different types are separated properly and samples with similar fluid-flow properties are classified in the same group, then this leads to finding an appropriate permeability/porosity relationship. In particular, the concept of hydraulic flow units (HFU) is used to characterize different rock types. This leads to a new physical-based permeability/porosity relationship that has two regression constants which are determined from the HFU method. These coefficients, which are obtained for several rock types in this study, may not be applicable to other carbonate rocks; but, by using the general form of the model presented here, based on the HFU method, one may obtain the value of these coefficients for any carbonate rock types. Finally, we used the data of cored wells for the validation of the permeability results

Analysis of well testing results for single phase flow in reservoirs with percolation structure

Constructing an accurate geological model of the reservoir is a preliminary to make any reliable prediction of a reservoir’s performance. Afterward, one needs to simulate the flow to predict the reservoir’s dynamic behaviour. This process usually is associated with high computational costs. Therefore, alternative methods such as the percolation approach for rapid estimation of reservoir efficiency are quite desirable. This study tries to address the Well Testing (WT) interpretation of heterogeneous reservoirs, constructed from two extreme permeabilities, 0 and K. In particular, we simulated a drawdown test on typical site percolation mediums, occupied to fraction “p” at a constant rate Q/h, to compute the well-known pressure derivative (dP/dlnt). This derivative provides us with “apparent” permeability values, a significant property to move forward with flow prediction. It is good to mention that the hypothetical wellbore locates in the middle of the reservoir with assumed conditions. Commercial software utilized to perform flow simulations and well test analysis. Next, the pressure recorded against time at different realizations and values of p. With that information provided, the permeability of the medium is obtained. Finally, the permeability change of this reservoir is compared to the permeability alteration of a homogeneous one and following that, its dependency on the model parameters has been analysed. The result shows a power-law relation between average permeability (considering all realizations) and the occupancy probability “p”. This conclusion helps to improve the analysis of well testing for heterogeneous reservoirs with percolation structures

Characterization and estimation of reservoir properties in a carbonate reservoir in Southern Iran by fractal methods

Abstract Reservoir heterogeneity has a major effect on the characterization of reservoir properties and consequently reservoir forecast. In reality, heterogeneity is observed in a wide range of scales from microns to kilometers. A reasonable approach to study this multi-scale variations is through fractals. Fractal statistics provide a simple way of relating variations on larger scales to those on smaller scales and vice versa. Simple statistical fractal models (fBm and fGn) can be useful to understand the model construction and help the reservoir structure characterization. In this paper, the fractal methods (fGn and fBm) have been applied to characterize and to estimate of reservoir properties. Three methods, namely box-counting, variogram, and R/S analysis, were carried out on log and core data for porosity and permeability data to estimate fractal dimension; a high fractal dimension estimated in this study reveals a high heterogeneity in the reservoir. Moreover, sampling from simulated fractal data at non-existing data depths enables us to generate appropriate realizations of reservoir permeability with suitable accuracy at a proper computational time

Comparison of Simulated Annealing, Genetic, and Tabu Search Algorithms for Fracture Network Modeling

Abstract The mathematical modeling of fracture networks is critical for the exploration and development of natural resources. Fractures can help the production of petroleum, water, and geothermal energy. They also greatly influence the drainage and production of methane gas from coal beds. Orientation and spatial distribution of fractures in rocks are important factors in controlling fluid flow. The objective function recently developed b

Comparison of Simulated Annealing, Genetic, and Tabu Search Algorithms for Fracture Network Modeling

The mathematical modeling of fracture networks is critical for the exploration and development of natural resources. Fractures can help the production of petroleum, water, and geothermal energy. They also greatly influence the drainage and production of methane gas from coal beds. Orientation and spatial distribution of fractures in rocks are important factors in controlling fluid flow. The objective function recently developed by Masihi et al. 2007 was used herein to generate fracture models that incorporate field observations. To extend this method, simulated annealing, genetic, and tabu search algorithms were employed in the modeling of fracture networks. The effectiveness of each algorithm was compared and the applicability of the methodology was assessed through a case study. It is concluded that the fracture model generated by simulated annealing is better compared to those generated by genetic and tabu search algorithms