Prediction of Rate of Penetration for wells at Nam Con Son basin using Artificial Neural Networks models

The rate of penetration (ROP) is an important parameter that affects the success of a drilling operation. In this paper, the research approach is based on different artificial neural network (ANN) models to predict ROP for oil and gas wells in Nam Con Son basin. The first is the process of collecting and evaluating drilling parameters as input data of the model. Next is to find the network model capable of predicting ROP most accurately. After that, the study will evaluate the number of input parameters of the network model. The ROP prediction results obtained from different ANN models are also compared with traditional models such as the Bingham model, Bourgoyne & Young model. These results have shown the competitiveness of the ANN model and its high applicability to actual drilling operations.

A Novel Artificial Neural Network-Based Correlation for Evaluating the Rate of Penetration in a Natural Gas Bearing Sandstone Formation: A Case Study in a Middle East Oil Field

This study presented an empirical correlation to estimate the drilling rate of penetration (ROP) while drilling into a sandstone formation. The equation developed in this study was based on the artificial neural networks (ANN) which was learned to assess the ROP from the drilling mechanical parameters. The ANN model was trained on 630 datapoints collected from five different wells; the suggested equation was then tested on 270 datapoints from the same training wells and then validated on three other wells. The results showed that, for the training data, the learned ANN model predicted the ROP with an AAPE of 7.5%. The extracted equation was tested on data gathered from the same training wells where it estimated the ROP with AAPE of 8.1%. The equation was then validated on three wells, and it determined the ROP with AAPEs of 9.0%, 10.7%, and 8.9% in Well-A, Well-B, and Well-D, respectively. Compared with the available empirical equations, the equation developed in this study was most accurate in estimating the ROP.

Optimization of Hot-Water Drilling in Ice with Near-Bottom Circulation

Hot-water drilling in ice with near-bottom circulation is more advantageous than traditional hot-water drilling with all-over borehole circulation in terms of power consumption and weight. However, the drilling performance of this type of drill has been poorly studied. Initial experiments showed that drilling with single-orifice nozzles did not proceed smoothly. To achieve the best drilling performance, nozzles with different orifice numbers and structures are evaluated in the present study. The testing results show that a single-orifice nozzle with a 3 mm nozzle diameter and a nine-jet nozzle with a forward angle of 35° had the highest rate of penetration (1.7–1.8 m h−1) with 5.6–6.0 kW heating power. However, the nozzles with backward holes ensured a smoother drilling process and a larger borehole, although the rate of penetration was approximately 13% slower. A comparison of the hollow and solid thermal tips showed that under the same experimental conditions, the hollow drill tip had a lower flow rate, higher outlet temperature, and higher rate of penetration. This study provides a prominent reference for drilling performance prediction and drilling technology development of hot-water drilling in ice with near-bottom circulation.

COMPRESSIVE CAPACITY OF HELICAL PILE FOUNDATION ON PEAT WITH VARIATION OF HELICAL PLATE DIAMETER

<p>The use of helical foundations to support structures on peat soil is still a new method. Research is needed to develop this foundation. There are 6 types of helical foundation tested on peat soil. To study the effect of helical plate diameter, plate diameters were varied with sizes 25 cm (M), 35 cm (L), and 45 cm (G). Plate positions (1, 2, 3 plates) are designed at 300 mm spacing. The axial compression bearing capacity test is carried out based on the constant rate of penetration procedure. At the beginning of loading, the load increases significantly. At a certain descent, the load begins to decrease slowly. The load-settlement curve shows that the larger the plate diameter, the greater the load it can withstand. The largest bearing capacity is produced by the GGG 30 foundation (3 plates dia.45 cm), which is 10.83 kN. LLL 30 helical foundation (3 plates dia.30 cm) provides a bearing capacity of 7.14 kN. These results clearly explain that the increase in plate diameter is directly proportional to the increase in the axial compression bearing capacity.</p>

Assessment of rate of penetration of a tunnel boring machine in the longest railway tunnel of Turkey

One of the most important issues in tunnels to be constructed with tunnel boring machines (TBMs) is to predict the excavation time. Excavation time directly affects tunnel costs and feasibility. For this reason, studies on the prediction of TBM performance have always been interesting for tunnel engineers. Therefore, the purpose of the study is to develop models to predict the rate of penetration (ROP) of TBMs. In accordance with the purpose of the study, a new database including 5334 cases is obtained from the longest railway tunnel of Turkey. Each case includes uniaxial compressive strength, Cerchar Abrasivity Index, α angle, weathering degree and water conditions as input or independent variables. Two multiple regression models and two ANN models are developed in the study. The performances of the ANN models are considerably better than those of the multiple regression equations. Before deep tunnel construction in a metamorphic rock medium, the ANN models developed in the study are reliable and can be used. In contrast, the performances of the multiple regression equations are promising, but they predict lower ROP values than the measured ROP values. Consequently, the prediction models for ROP are open to development depending on the new data and new prediction algorithms.

A stacked generalization ensemble model for optimization and prediction of the gas well rate of penetration: a case study in Xinjiang

In gas drilling operations, the rate of penetration (ROP) parameter has an important influence on drilling costs. Prediction of ROP can optimize the drilling operational parameters and reduce its overall cost. To predict ROP with satisfactory precision, a stacked generalization ensemble model is developed in this paper. Drilling data were collected from a shale gas survey well in Xinjiang, northwestern China. First, Pearson correlation analysis is used for feature selection. Then, a Savitzky-Golay smoothing filter is used to reduce noise in the dataset. In the next stage, we propose a stacked generalization ensemble model that combines six machine learning models: support vector regression (SVR), extremely randomized trees (ET), random forest (RF), gradient boosting machine (GB), light gradient boosting machine (LightGBM) and extreme gradient boosting (XGB). The stacked model generates meta-data from the five models (SVR, ET, RF, GB, LightGBM) to compute ROP predictions using an XGB model. Then, the leave-one-out method is used to verify modeling performance. The performance of the stacked model is better than each single model, with R2 = 0.9568 and root mean square error = 0.4853 m/h achieved on the testing dataset. Hence, the proposed approach will be useful in optimizing gas drilling. Finally, the particle swarm optimization (PSO) algorithm is used to optimize the relevant ROP parameters.

Experimental study on rock-breaking mechanism of micro-coring PDC bit

In this paper, in order to study the rock-breaking mechanism of the micro-coring PDC bit, a series of unit breaking experiments containing 2 breaking forms (static-pressure breaking and fracture breaking) are conducted on core columns of sandstone, limestone, and granite. Besides, a full-sized micro-coring PDC bit with a diameter of 152.4 mm is designed and manufactured and is used to conduct an indoor experiment on multiple sized sandstone core columns. The unit breaking experiment results show that ROP (rate of penetration) of the fracture breaking is higher than the static-pressure breaking. The indoor experiment results of the full-sized bit show that ROP of the micro-coring PDC bit is 49–112% higher than the conventional bit and that the diameter of core column shows greater influence on ROP, while the height of the column shows smaller. Moreover, the micro-coring PDC bit realizes volumetric fracture on all of the three types of rock samples. Since volumetric fracture produces large rock debris, the rock-breaking efficiency and ROP of the micro-coring PDC bit will be improved significantly.

Optimizing Directional Drilling While Simultaneously Maximizing the Whole Life Value of the Well

Increasingly complex wells and longer laterals present new challenges for wellbore placement and wellbore quality. There is a growing understanding of the impact of well placement and wellbore quality on the overall value of the well and on the economics of completions and production. This paper looks at how requirements have evolved and will evolve beyond simply "getting to TD" as quickly as possible and how emerging technologies can help. There is already an undercurrent of opinion that completions and production are sometimes compromised to maximize rate of penetration, but with some controversy about the exact value and how easy it is to attribute cause. This paper reviews how directional drilling practice has evolved over 100 years, and how the wellbore quality that results from the directional drilling process can be a driver for the overall value of the well. Specifically, it draws on a number of key references to examine how tortuosity doesn't just have an influence on drilling but also how it can adversely impact completions, reliability of production equipment and even production rates. The paper proposes that we consider the whole-life value of the well as a key performance indicator as we drill. It emphasises that we must cease to focus solely on rate of penetration and the depth-time curve. The paper shows, with examples, how modern directional drilling systems can address tortuosity and improve wellbore quality. It presents an unbiased view of the industry from an independent viewpoint, exploring how directional drilling has been partially automated over the years and examining the state of the art in current automated directional drilling systems. It proposes the need for a modern directional drilling system not just in terms of drilling parameters but also in terms of automation of geometric and, ultimately, geologic aspects of directional drilling. The paper is intended to break down the silos that can exist between drilling, completions and production functions, and to help the industry to think about the long-term consequences of performance when specifying future directional drilling equipment.