scholarly journals Rate Decline Analysis for Horizontal Wells with Multiple Sections

Geofluids ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Jiazheng Qin ◽  
Shiqing Cheng ◽  
Youwei He ◽  
Dingyi Li ◽  
Jia Zhang ◽  
...  
Keyword(s):  
History Matching ◽  
Horizontal Well ◽  
Oil And Gas ◽  
Production Performance ◽  
Total Production ◽  
Type Curves ◽  
Decline Curves ◽  
Compound Type ◽  
Horizontal Wellbore ◽  
Sensitive Parameters

The widely used application of horizontal well makes it significant to effectively evaluate rate performance of horizontal well in oil and gas reservoir. However, most models in previous work only focus on rate decline analysis (RDA) of horizontal well with single section (HWSS); they hardly address the problem that production rate distributes nonuniformly along horizontal wellbore in analyzing rate transient behaviors. However, only some horizontal segments contribute to the total production rates, and the production of each section along horizontal wellbore is not the same in fact, which may be caused by reservoir heterogeneity, selective completion, and nonuniform formation damage along horizontal wellbore. Therefore, the effect of these phenomena on rate decline characteristics cannot be ignored. The aim of this paper is to propose an analytical model to investigate transient rate response of a horizontal well with multiple sections (HWMS). The compound type curves, including the normalized production curve, the normalized production integral curve, and the production integral derivative curve, are developed to distinguish the different cases. The influences of some sensitive parameters on decline curves are further discussed. Results show obvious differences on the decline curves between the HWMS and HWSS. The parameters are sensitive on decline curves, which explore the feasible application on production performance evaluation and parameters interpretation through history matching the production data with the compound type curves in this paper.

Decline Curve Analysis of Fractured Horizontal Wells Through Segmented Fracture Model

2018 ◽  
Vol 141 (1) ◽  
Author(s):  
Jiazheng Qin ◽  
Shiqing Cheng ◽  
Youwei He ◽  
Yang Wang ◽  
Dong Feng ◽  
...  
Keyword(s):  
Production Rate ◽  
History Matching ◽  
Curve Analysis ◽  
Production Performance ◽  
Fracture Model ◽  
Total Production ◽  
Type Curves ◽  
Decline Curve Analysis ◽  
Decline Curve ◽  
Compound Type

Nowadays, production performance evaluation of a multifractured horizontal well (MFHW) has attracted great attention. This paper presents a mathematical model of an MFHW with considering segmented fracture (SF) for better evaluation of fracture and reservoir properties. Each SF consists of two parts: fracture segment far from wellbore (FSFW) and fracture segment near to wellbore (FSNW) in segmented fracture model (SFM), which is different from fractures consists of only one segment in common fracture model (CFM). Employing the source function and Green's function, Newman's product method, Duhamel principle, Stehfest inversion algorithm, and Laplace transform, production solution of an MFHW can be obtained using SFM. Total production rate is mostly contributed from FSNW rather than FSFW in many cases; ignoring this phenomenon may lead to obvious erroneous in parameter interpretation. Thus, clear distinctions can be found between CFM and SFM on the compound type curves. By using decline curve analysis (DCA), the influences of sensitive parameters (e.g., dimensionless half-length, dimensionless production rate, conductivity, and distance between SF) on compound type curves are analyzed. The results of sensitivity analysis are benefit of parameter estimation during history matching.

scholarly journals Horizontal Well Completion with Multiple Artificial Bottom Holes Improves Production Performance in Bottom Water Reservoir

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Haidong Wang ◽  
Yikun Liu
Keyword(s):  
Pressure Distribution ◽  
Horizontal Well ◽  
Bottom Water ◽  
New Technology ◽  
Water Reservoir ◽  
Pressure Profile ◽  
Production Performance ◽  
Well Completion ◽  
Horizontal Wellbore ◽  
Control Technologies

The horizontal well completion with stinger is usually used to control the bottom water cone. Although the pressure profile and the inflow profile along the horizontal wellbore can be divided into two parts by the stinger, these profiles have not really flattened. In order to flatten the pressure distribution and inflow distribution further, it proposes a new technology. This new horizontal well has multiple artificial bottom holes (MABH) along the wellbore and it has application potential. In order to verify the effectiveness of MABH technology, a model of horizontal well completion with MABH was established, and the production performance of different water cone control technologies was analyzed: conventional horizontal well, stinger completion horizontal well, and MABH completion horizontal well. The results show that the MABH technology has more advantages than the stinger technology. The uniformity of pressure distribution of the 6-MABH horizontal well is 55% higher than that of the horizontal well with string technology, and the uniformity of inflow distribution is increased by 65.25%. At the same time, although the operation of MABH technology is very simple, it should follow a rule of MABH installation: the position of the first MABH should be set at 242.5 m from the heel hole of the horizontal wellbore, and the other interval is 92.4 m.

Design of Horizontal Wellbore in Dadas Shales of Turkey by Considering Wellbore Stability and Reservoir Geomechanics

2021 ◽  
Author(s):  
Sukru Merey ◽  
Can Polat ◽  
Tuna Eren
Keyword(s):  
Hydraulic Fracturing ◽  
Horizontal Well ◽  
Oil And Gas ◽  
Horizontal Wells ◽  
Horizontal Stress ◽  
Wellbore Stability ◽  
Horizontal Drilling ◽  
Horizontal Wellbore ◽  
Reservoir Geomechanics ◽  
Maximum Horizontal Stress

Abstract Currently, many horizontal wells are being drilled in Dadas shales of Turkey. Dadas shales have both oil (mostly) and gas potentials. Thus, hydraulic fracturing operations are being held to mobilize hydrocarbons. Up to 1000 m length horizontal wells are drilled for this purpose. However, there is not any study analyzing wellbore stability and reservoir geomechanics in the conditions of Dadas shales. In this study, the directions of horizontal wells, wellbore stability and reservoir geomechanics of Dadas shales were designed by using well log data. In this study, the python code developed by using Kirsch equations was developed. With this python code, it is possible to estimate unconfined compressive strength in along wellbore at different deviations. By analyzing caliper log, density and porosity logs of Dadas shales, vertical stress of Dadas shales was estimated and stress polygon for these shale was prepared in this study. Then, optimum direction of horizontal well was suggested to avoid any wellbore stability problems. According to the results of this study, high stresses are seen in horizontal directions. In this study, it was found that the maximum horizontal stress in almost the direction of North-South. The results of this study revealed that direction of maximum horizontal stress and horizontal well direction fluid affect the wellbore stability significantly. Thus, in this study, better horizontal well design was made for Dadas shales. Currently, Dadas shales are popular in Turkey because of its oil and gas potential so horizontal drilling and hydraulic fracturing operations are being held. However, in literature, there is no study about horizontal wellbore designs for Dadas shales. This study will be novel and provide information about the horizontal drilling design of Dadas shales.

scholarly journals Evaluation of Reservoir Quality and Forecasted Production Variability along a Multi-Fractured Horizontal Well. Part 2: Selected Stage Forecasting

Energies ◽  
2021 ◽  
Vol 14 (19) ◽  
pp. 6007 ◽  
Author(s):  
Christopher R. Clarkson ◽  
Zhenzihao Zhang ◽  
Farshad Tabasinejad ◽  
Daniela Becerra ◽  
Amin Ghanizadeh
Keyword(s):  
History Matching ◽  
Horizontal Well ◽  
Production Performance ◽  
Reservoir Quality ◽  
Well Performance ◽  
Fracture Geometry ◽  
Fractured Horizontal Well ◽  
Production Variability ◽  
Montney Formation ◽  
Low Permeability Reservoirs

The current practice for multi-fractured horizontal well development in low-permeability reservoirs is to complete the full length of the well with evenly spaced fracture stages. Given methods to evaluate along-well variability in reservoir quality and to predict stage-by-stage performance, it may be possible to reduce the number of stages completed in a well without a significant sacrifice in well performance. Provision and demonstration of these methods is the goal of the current two-part study. In Part 1 of this study, reservoir and completion quality were evaluated along the length of a horizontal well in the Montney Formation in western Canada. In the current (Part 2) study, the along-well reservoir property estimates are first used to forecast per-stage production variability, and then used to evaluate production performance of the well when fewer stages are completed in higher quality reservoir. A rigorous and fast semi-analytical model was used for forecasting, with constraints on fracture geometry obtained from numerical model history matching of the studied Montney well flowback data. It is concluded that a significant reduction in the number of stages from 50 (what was implemented) to less than 40 could have yielded most of the oil production obtained over the forecast period.

AI, Data Analytics Enable Approach to History Matching in Geologically Complex Field

2021 ◽  
Vol 73 (04) ◽  
pp. 58-59
Author(s):  
Judy Feder
Keyword(s):  
Artificial Intelligence ◽  
Data Analytics ◽  
History Matching ◽  
Oil And Gas ◽  
Production Performance ◽  
Asia Pacific ◽  
Reservoir Modeling ◽  
Complex Field ◽  
Reservoir Model ◽  
New Approach

This article, written by JPT Technology Editor Judy Feder, contains highlights of paper SPE 202460, “History Matching of Production Performance for Highly Faulted, Multilayered, Clastic Oil Reservoirs Using Artificial Intelligence and Data Analytics: A Novel Approach,” by Nis Ilyani Mohmad and Dipak Mandal, SPE, Petronas, and Hadi Amat, Petroliam Nasional, et al., prepared for the 2020 SPE Asia Pacific Oil and Gas Conference and Exhibition, originally scheduled to be held in Perth, Australia, 20-22 October. The paper has not been peer reviewed. History matching is a critical step for dynamic reservoir modeling to establish a reliable, predictive model. Numerous approaches have emerged over decades to accomplish a robust history-matched reservoir model. As geological and completion complexity of oil and gas fields increase, building a fully representative predictive reservoir model can be arduous to almost impossible. The complete paper outlines an approach to history matching that uses artificial intelligence (AI) with an artificial neural network (ANN) and data-driven analytics. The new approach has been used to mitigate history-matching challenges in a mature, highly geologically complex field offshore Malaysia. Overview The complete paper describes a step-by-step methodology for building a reservoir model and a history-matching process using ANN. The paper discusses data preparation and quality assurance and control (QA/QC), spatiotemporal database formulation, reservoir model design, ANN architecture design, model training, and history-matching strategy. A case study of implementation in an offshore Malaysian field is presented, wherein good-to-fair history-matching quality was obtained for all production parameters. Field A is a highly geologically complex, 25×75-km oil sandstone reservoir with more than 200 major and minor faults and more than 30 reservoir layers. It has been producing for more than 25 years. The challenges of history matching this field lie not only in its geologically complex structure and corresponding subsurface uncertainties, but also in a production strategy that has involved commingled dual-string production with several integrity issues that exacerbate the field’s complexities. To date, Field A has no fieldwide history-matched reservoir model because the complexity of history matching has precluded using conventional numerical simulation methods. This challenge has been mitigated by implementing an AI-based reservoir model and data analytics. The new approach is estimated to be more time- and cost-efficient than the conventional method. The complete paper compares the AI-based and conventional numerical reservoir modeling approaches and highlights the advantages, limitations, and areas of improvement of the new methodology. The authors present their case for AI-based reservoir modeling as a complement or alternative to conventional numerical modeling to create time-efficient reservoir models while reducing risk in field-development plans.

scholarly journals Production behavior evaluation on multilayer commingled stress-sensitive carbonate gas reservoir

2020 ◽  
pp. 014459872096415
Author(s):  
Jianlin Guo ◽  
Fankun Meng ◽  
Ailin Jia ◽  
Shuo Dong ◽  
Haijun Yan ◽  
...  
Keyword(s):  
Early Stage ◽  
Sedimentary Environment ◽  
Production Performance ◽  
Total Production ◽  
Inversion Algorithm ◽  
Gas Reservoir ◽  
Hole Pressure ◽  
Bottom Hole Pressure ◽  
Bottom Hole ◽  
Production Behavior

Influenced by the complex sedimentary environment, a well always penetrates multiple layers with different properties, which leads to the difficulty of analyzing the production behavior for each layer. Therefore, in this paper, a semi-analytical model to evaluate the production performance of each layer in a stress-sensitive multilayer carbonated gas reservoir is proposed. The flow of fluids in layers composed of matrix, fractures, and vugs can be described by triple-porosity/single permeability model, and the other layers could be characterized by single porosity media. The stress-sensitive exponents for different layers are determined by laboratory experiments and curve fitting, which are considered in pseudo-pressure and pseudo-time factor. Laplace transformation, Duhamel convolution, Stehfest inversion algorithm are used to solve the proposed model. Through the comparison with the classical solution, and the matching with real bottom-hole pressure data, the accuracy of the presented model is verified. A synthetic case which has two layers, where the first one is tight and the second one is full of fractures and vugs, is utilized to study the effects of stress-sensitive exponents, skin factors, formation radius and permeability for these two layers on production performance. The results demonstrate that the initial well production is mainly derived from high permeable layer, which causes that with the rise of formation permeability and radius, and the decrease of stress-sensitive exponents and skin factors, in the early stage, the bottom-hole pressure and the second layer production rate will increase. While the first layer contributes a lot to the total production in the later period, the well bottom-hole pressure is more influenced by the variation of formation and well condition parameters at the later stage. Compared with the second layer, the scales of formation permeability and skin factor for first layer have significant impacts on production behaviors.

scholarly journals Efficient Dimensionality Reduction Methods in Reservoir History Matching

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3137
Author(s):  
Amine Tadjer ◽  
Reider B. Bratvold ◽  
Remus G. Hanea
Keyword(s):  
Data Assimilation ◽  
Dimensionality Reduction ◽  
Gaussian Process ◽  
Latent Variable ◽  
History Matching ◽  
Production Performance ◽  
Latent Variable Model ◽  
Variable Model ◽  
Multiple Data ◽  
Ensemble Smoother

Production forecasting is the basis for decision making in the oil and gas industry, and can be quite challenging, especially in terms of complex geological modeling of the subsurface. To help solve this problem, assisted history matching built on ensemble-based analysis such as the ensemble smoother and ensemble Kalman filter is useful in estimating models that preserve geological realism and have predictive capabilities. These methods tend, however, to be computationally demanding, as they require a large ensemble size for stable convergence. In this paper, we propose a novel method of uncertainty quantification and reservoir model calibration with much-reduced computation time. This approach is based on a sequential combination of nonlinear dimensionality reduction techniques: t-distributed stochastic neighbor embedding or the Gaussian process latent variable model and clustering K-means, along with the data assimilation method ensemble smoother with multiple data assimilation. The cluster analysis with t-distributed stochastic neighbor embedding and Gaussian process latent variable model is used to reduce the number of initial geostatistical realizations and select a set of optimal reservoir models that have similar production performance to the reference model. We then apply ensemble smoother with multiple data assimilation for providing reliable assimilation results. Experimental results based on the Brugge field case data verify the efficiency of the proposed approach.

Gravity Drainage System: Investigation and Field Development Using Geological Modelling and Reservoir Simulation

2021 ◽  
Author(s):  
Obinna Somadina Ezeaneche ◽  
Robinson Osita Madu ◽  
Ishioma Bridget Oshilike ◽  
Orrelo Jerry Athoja ◽  
Mike Obi Onyekonwu
Keyword(s):  
Reservoir Simulation ◽  
Structural Control ◽  
History Matching ◽  
Drainage System ◽  
Production Performance ◽  
Gravity Drainage ◽  
Base Case ◽  
Proper Understanding ◽  
Field Development ◽  
Reservoir Performance

Abstract Proper understanding of reservoir producing mechanism forms a backbone for optimal fluid recovery in any reservoir. Such an understanding is usually fostered by a detailed petrophysical evaluation, structural interpretation, geological description and modelling as well as production performance assessment prior to history matching and reservoir simulation. In this study, gravity drainage mechanism was identified as the primary force for production in reservoir X located in Niger Delta province and this required proper model calibration using variation of vertical anisotropic ratio based on identified facies as against a single value method which does not capture heterogeneity properly. Using structural maps generated from interpretation of seismic data, and other petrophysical parameters from available well logs and core data such as porosity, permeability and facies description based on environment of deposition, a geological model capturing the structural dips, facies distribution and well locations was built. Dynamic modeling was conducted on the base case model and also on the low and high case conceptual models to capture different structural dips of the reservoir. The result from history matching of the base case model reveals that variation of vertical anisotropic ratio (i.e. kv/kh) based on identified facies across the system is more effective in capturing heterogeneity than using a deterministic value that is more popular. In addition, gas segregated fastest in the high case model with the steepest dip compared to the base and low case models. An improved dynamic model saturation match was achieved in line with the geological description and the observed reservoir performance. Quick wins scenarios were identified and this led to an additional reserve yield of over 1MMSTB. Therefore, structural control, facies type, reservoir thickness and nature of oil volatility are key forces driving the gravity drainage mechanism.

Compatibility Study of Condensate and Heavy Oil for Storage in an Iranian Reservoir

2021 ◽  
pp. 1-13
Author(s):  
K. Zobeidi ◽  
M. Ganjeh-Ghazvini ◽  
V. Hematfar
Keyword(s):  
Heavy Oil ◽  
Oil And Gas ◽  
Production Performance ◽  
Compatibility Study ◽  
Asphaltene Precipitation ◽  
High Concentration ◽  
Full Capacity ◽  
Potential Risks ◽  
Operational Criteria ◽  
Positive Effect

Summary During the years 2017–2020, when Iran faced restrictions on the sale of oil and gas condensate and due to the need for domestic consumption and gas sales commitments, it was inevitable to produce gas at full capacity. This coercion has led to significant production of gas condensates. Some of these condensates were sold, some were converted into products such as gasoline in domestic refineries, and some of these condensates needed to be stored, but the storage capacity was limited. For the purpose of underground condensate storage, a heavy oil reservoir was selected based on some technical and operational criteria. A feasibility study was conducted to evaluate the potential risks of condensate injection into the reservoir. The results of tests on asphaltene precipitation, as the most important risk, indicated no severe precipitation would occur even if high concentration of condensate mixed with the reservoir heavy oil. The recovery of condensate and the production performance of the reservoir were simulated in three different injection-production scenarios. The results showed a positive effect of condensate injection on production rate of the reservoir. Moreover, satisfactory volume of condensate could be recovered in a reasonable period of time.

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