Permeability is a key parameter related to any hydrocarbon reservoir characterization. Moreover, many petroleum engineering problems cannot be precisely answered without having accurate permeability value. Core analysis and well test techniques are the conventional methods determine permeability. These time-consuming very expensive. Therefore, researches have been introduced identify relationship between core log data using artificial neural network (ANN). The objective of this research...

The rheological properties of the drilling fluid play a key role in controlling operation. Knowledge is very crucial for hydraulic calculations required hole cleaning optimization. Measuring during sometimes time-consuming process. Wrong estimation these may lead to many problems, such as pipe sticking, loss circulation, and/or well control issues. aforementioned problems increase non-productive time and overall cost operations. In this paper, frequent measurements (mud density, Marsh funnel...

In this study, we used artificial neural networks (ANN) to estimate static Young’s modulus (Estatic) for sandstone formation from conventional well logs. ANN design parameters were optimized using the self-adaptive differential evolution optimization algorithm. The model was trained predict Estatic logs of bulk density, compressional time, and shear time. on 409 data points one well. extracted weights biases develop an empirical relationship estimation based This correlation tested 183...

Rate of penetration (ROP) is one the most important drilling parameters for optimizing cost hydrocarbon wells. In this study, a new empirical correlation based on an optimized artificial neural network (ANN) model was developed to predict ROP alongside horizontal carbonate reservoirs as function parameters, such rotation speed, torque, and weight-on-bit, combined with conventional well logs, including gamma-ray, deep resistivity, formation bulk density. The ANN trained using 3000 data points...

The fracture volume is gradually changed with the depletion of pressure during production process. However, there are few flowback models available so far that can estimate loss using transient and rate data. initial involves producing back fracturing fluid after hydraulic fracturing, while second preloading injected into parent wells before child wells. main objective this research to compare data capture changes in preload processes. Such a comparison useful for evaluating well performance...

Rock mechanical properties play a key role in the optimization process of engineering practices oil and gas industry so that better field development decisions can be made. Estimation these is central well placement, drilling programs, completion design. The elastic behavior rocks studied by determining two main parameters: Young’s modulus Poisson’s ratio. Accurate determination ratio helps to estimate in-situ horizontal stresses turn, avoid many critical problems which interrupt operations,...

Reservoir fluid properties such as bubble point pressure (Pb) and gas solubility (Rs) play a vital role in reservoir management simulation. In addition, they affect the design of production system. Pb Rs can be obtained from laboratory experiments by taking sample at wellhead or under downhole conditions. However, this process is time-consuming very costly. To overcome these challenges, empirical correlations artificial intelligence (AI) models applied to obtain properties. The objective...

Abstract Geomechanical failure parameters are best estimated from core samples, which not always available. To address this, numerous relationships have been proposed that relate rock strength to measurable with geophysical well logs, but they tend limited accuracy or low range of applicability. This paper aims at overcoming the limitations existing techniques by using different artificial intelligence (AI). The data used in this study usually available commonly conducted log surveys...

Determination of optimal well locations plays an important role in the efficient recovery hydrocarbon resources. However, it is a challenging and complex task. The objective this paper to determine heavy oil reservoir under production using novel process which steam generated, situ, thermochemical reactions. Self-adaptive differential evolution (SaDE) particle swarm optimization (PSO) methods are used as global optimizer find configuration wells that will yield highest net present value...

Summary The heterogeneity of tight reservoirs, along with their complex geologic characteristics and the diverse completion practices used, presents challenges in developing accurate models to forecast productivity for multifractured horizontal wells (MFHWs) completed these reservoirs. This paper introduces a new early-time diagnostic tool that leverages two-phase flowback data long-term evaluate efficiency. To achieve this, two novel were developed. first model, water/oil-ratio model...

This paper introduces a novel approach to generate downhole steam using thermochemical reactions overcome the challenges associated with heavy oil resources. The procedure developed in this is applied reservoir, which contains (12–23 API) an estimated range of original place (OOIP) 13–25 billion barrels while its several technical are limiting commercial development. One these overlying 1800–2000-ft thick permafrost layer, causes significant heat losses when injected from surface facilities....

Abstract Heavy oil has attracted global attention due to its huge volume of original in place. However, there are numerous operation and economic challenges during the recovery heavy high-viscosity high-density. Thermal methods such as steam injection is viable commonly used recover bitumen primarily by thermally altering viscosity improving displacement oil. significant heat losses before reaches oil, addition concerns high cost emission greenhouse gases. One promising new approaches...

Abstract Hydraulic fracturing combined with horizontal drilling is the key to unlocking vast unconventional reservoirs. However, understanding relationship between fracturing/completion-design parameters and process efficiency remains challenging. The objectives of this paper are 1) estimate initial fracture volume its variations during production by using flowback data 2) investigate existence correlations completion-design induced optimization. We analyze 16 shale-gas completed in Eagle...

Abstract Bubble point pressure (Pb) and gas solubility (Rs) are reservoir fluid properties that have significant effect on oil characterization engineering computations. Better knowledge of these PVT improve the reliability simulation. Perfectly, should be obtained from actual laboratory measurements. However, measurements either not available or very costly to obtained. For reasons, there is a need for quick reliable method predicting properties. There numerous approaches properties,...

Abstract Alaska North Slope (ANS) contains heavy oil (12-23 API) with an estimated range of original in place (OOIP) 13 to 25 billion barrels. This resource has been considered as one the largest deposits United States. However, several technical challenges are limiting its commercial development. One most significant difficulty is overlying 1,800-2,000 ft-thick permafrost layer, which causes unavoidable heat losses when steam injected from surface generators, and potentially disastrous...

Abstract Heavy oil has attracted global attention due to its huge volume of original in place. However, there are numerous operation and economic challenges the recovery heavy high-viscosity high-density. Thermal methods such as steam injection is viable commonly used recover bitumen primarily by viscosity reduction improving displacement oil. significant heat losses before reaches heavy-oil reservoir, addition concerns high cost emission greenhouse gases. One promising new approaches...

The Publisher regrets that this article is an accidental duplication of has already been published, http://dx.doi.org/10.2118/187976-MS. duplicate therefore withdrawn. full Elsevier Policy on Article Withdrawal can be found at https://www.elsevier.com/about/our-business/policies/article-withdrawal

Abstract Static Young's modulus (Estatic) is an essential parameter needed to develop the earth geomechanical model, (E) considerably varies with change in lithology. Recently, artificial intelligence (AI) techniques were used estimate Estatic for carbonate formation. In this study, neural network (ANN) was sandstone ANN design parameters optimized using self-adaptive differential evolution (SaDE) optimization algorithm. The model trained predict from conventional well log data such as bulk...

The mechanical behavior of the rocks can greatly assist in optimizing drilling operation and well completion design. This be expressed terms Young’s modulus Poisson’s ratio. Reliable ratio values estimated experimentally from core measurements however this method consumes time economically ineffective. study involved development two models using neural networks (ANN) fuzzy logic to estimate static (PRstatic) sandstone based on conventional well-log data including bulk density sonic log data....

Abstract Pore-scale images and core-scale imbibition experiments suggest that hydrocarbon water tend to flow through their own pore network, referred as "stratified flow". The objective of this paper is investigate the occurrence these phenomena at reservoir scale by analyzing flowback post-flowback production data. Understanding multiphase regimes first step for selecting proper relative permeability curves developing representative rate-transient models. Another harmonic decline (HD)...